I’m extremely happy to announce that this week I will start my (research) internship  at Sanoma Media, the biggest multimedia publisher in The Netherlands. The coming months I will be working at the Online Strategy and M&A department where I also will be writing my master thesis on Alliance portfolio management and open service innovation.  An excellent opportunity to gain experience in the field of acquisitions in the most interesting online/ditigal industry. I’m very grateful for this opportunity and would like to thank those who made it possible! Now I’m off to prepare myself for the reality of a just almost graduated MBA student with Excel tutorials.

How to get ThesisTools questionnaire data into SPSS

Thesistools is a free survey/questionnaire website that most of the Dutch students use to create their questionaires. Importing your Thesistools data into Spss can be done by following these steps.

1.       Go to the ThesisTools website > Modify Questionnaire. Login, click ‘Results’ and download the data as an Excel file.

2.       Open the Excel file (if you get a warning, just click ‘Yes’) . Delete the Page, Title and Legend rows.

3.       Rename what is now the top-left cell (‘Question’) into respondentID (or something like that). Also, you can delete any blank columns. The result is a nice, clean Excel file (see below). Save the file as an Excel (.xls) file . Close Excel.

4.       Open SPSS > File > Open Data, set “Type of files” to “Microsoft Excel (*.xls)”  and select your Excel file

5.      A dialogue screen will appear. Make sure that “Read variable names from the first row of data” is selected (which it is by default) and click ‘OK’.  SPSS should now have opened your file, which can later save a proper SPSS file (.sav file). For practical purposes, you may want to shorten the labels/names of the variables. You can do this by going to the ‘Variable View’ sheet.

SPSS Analyses of Survey Data tutorial

Introduction

This document contains a short description of the analyses that have to be performed on the data collected with the survey that is part of the BRM course. The aim of these analyses is to test your hypotheses by for instance getting insight into (1) the differences between groups within the organization or between different variables and (2) the relationships between different variables.

In this process, three main steps are distinguished:

1. Prepare data
2. Test operationalizations
3. Test theory (hypotheses)

Prepare data

First, we have to make sure the data are ready for further analyses. This concerns the following steps:

Check for errors

-          WHAT?
Make sure that there are no errors in the dataset, such as impossible values or other mistakes that would affect your analysis.

-          HOW?
- Look through the data set for strange things
- Get the descriptives for all items

-          WHERE?
- Analyze > Descriptives > Frequencies
- Analyze > Descriptives > Descriptives

Recode variables

-          WHAT?
Make sure that all items (= questions in the dataset) “point the same way”. Sometimes, the same concept is measured by items that are both positive and negative in terms of that concept. For instance, measuring attitude towards a product with items saying both “I like…” and “I dislike…”.

-          HOW?
Reverse the codes for items that “point the wrong way”. Recode into new variables, and change values from 5>1, 4>2, 3>3, 2>4 and 1>5.

-          WHERE?
Transform > Recode > into different variables

Make new variables for open questions (if necessary)

-          WHAT?
Some questions may be open questions, e.g. “What’s your function?”. If that is the case, you don’t have a variable you can use to compare groups (for instance). In that case, you have to make a new variables with categories (e.g., management, sales, engineering, etc.).

-          HOW?
Insert a new variable in the dataset, and manually assign categories to the different functions. Go through the dataset case per case.

-          WHERE?
Edit > Insert variables

Test operationalizations

Having gotten our data up to date, we can check for the quality of our operationalizations – in other words, the quality of the way we have measured our variables. Before continuing with the data analysis, we have to make sure that the measures we are basing our analyses on, are OK.

Reliability analysis

-          WHAT?
Test whether the different items that we assume to measure one variable, can indeed be taken together into one scale (e.g., kshare1 up to kshare8).

-          HOW?
Perform a reliability analysis. Pay attention to the following criteria:

o   Cronbach’s alpha (is this higher than .65?)

o   Corrected item-total correlation (higher than .30?)

o   Alpha if item deleted (can we relevantly improve reliability by deleting items?).

Based on these criteria, decide whether to continue with the scale, to delete some items or do away with the scale altogether.

-          WHERE?
- Analyze > Scale > Reliability Analysis
- You can click “Statistics” here and ask for Descriptives for scale, items and scale if item deleted.

Create scales

-          WHAT?
Create the scales that you have just determined to be sound measurements of the variables you are measuring.

-          HOW?
By adding the different items you have decided do belong together, or (preferably) computing the means of these sets of items. The advantage of using the means is that the scale will have scores between 1 to 5, and that you are able to compare the scores on different scales. Otherwise, you couldn’t compare the mean score on a scale consisting of 6 items (with scores ranging from 6 to 30) with the mean score on a scale with 8 items (with a range from 8 to 40).

-          WHERE?
Transform > Compute

o   The “target variable” is the scale you are creating (for instance, “kshare”).

o   The “numeric expression” would be the formula to create this scale, e.g.

§  Mean (kshare1, kshare2, kshare3,…, kshare8)

Test theory

The previous steps have left you with a dataset in which all the key concepts are represented by scales that are valid measurements of these concepts. You now have a scale for each relevant concept, and of course the first few questions in the survey that provide you information on functions, departments, length of employment etc. You can now use these scales and other variables to test assumptions about differences and relationships.

Test for differences

-          WHAT?
It is interesting to see whether (for instance) people fulfilling different positions in the organization score differently on relevant variables. Do high level experts share more knowledge than administrative personnel? Do managers have a more positive view of the organization than non-managers? Does IT have a more positive perception of IT performance than the business side?

-          HOW?
For differences between two groups: Perform a t-test. If you’re comparing two groups, choose the independent samples t-test. The grouping variable is the variable based on which you make groups – for instance, function, where group 1 is managers and group 2 is non-managers. The test variables are the variables for which you want to test whether the groups score differently (for instance, knowledge sharing). Pay attention to the following criteria in the output:

o   F-value and significance of F-value (undere “Levene’s test for Equality of Variances”). This value tells you nothing about the actual differences found, it basically tells you in which row of the output you should look for results. What’s tested here, is whether the variances of the scores of both groups on the test variable are equal or not. If they’re not, SPSS is extra cautious with a number of things. If the significance of this F-value is lower than .05, this means that the variances differ significantly – and that you can not assume that there are equal variances, in other words, you should look in the bottom row of the output. That’s where you look for the following statistics.

o   T-value: gives an indication of the strength of the difference.

o   Degrees of freedom.

o   Significance of t-value: this is the decisive statistic. If the t-value is significant, this means that there is a significant difference between the groups – in other words, that (for instance) high level experts share more knowledge than administrative personnel.

-          For differences between more than two groups: Perform an analysis of variance (ANOVA). The “Factor” is the variable determining your groups (for instance, “department”), the “Dependent List” contains the variables for which you want to test whether there are differences between these groups (for instance, knowledge sharing). Pay attention to the following criteria in the output:

o   F-value and significance of F-value. For this test, this is the decisive statistic: If the F-value is significant, this means that you have found a significant difference between the groups on this variable. Look at the descriptives (you can click that in the menu for the ANOVA) to get more insight into the actual nature of these differences.

o   The F-value and descriptives don’t provide a definitive insight into which of the groups you distinguish differ from each other. In order to be able to determine exactly which departments (for instance) score higher or lower than the other ones, click Post Hoc. Then, you can choose from a number of post hoc tests that do tell you which groups differ from each other. Common post hoc tests are LSD, Bonferroni and Tukey. LSD is relatively simple, as it performs a number of t-tests between each of the groups. If the F-value is not significant, doing a Post Hoc test does not make much sense. Then, the conclusion is that there are no differences.

-          WHERE?

o   T-test: Analyze > Compare Means > Independent Samples T-test

o   ANOVA: Analyze > Compare Means > One-way ANOVA

§  Don’t forget Post Hoc

Test for relationships between variables

-          WHAT?
Both theoretically and practically, you can have a lot of assumptions about relationships between variables. For instance, is a knowledge friendly organizational culture positively related to the level of relational social capital? Do the different dimensions of social capital explain the level of knowledge sharing in the organization?

-          HOW?
Correlations: If you’re only interested in the way variables are related, but not in the distinction between dependent and independent variables, you can compute correlations between these variables. Compute the Pearson correlation coefficient and see if the variables are positively related, negatively related, or not related at all. Pay attention to the following criteria in the output:

o   Pearson’s r: this tells you the strength and direction of the relationship. If this statistic is 1, there is perfectly positive correlation, if it is -1, there is a perfectly negative correlation, and if it is 0, there is no correlation. In practice, of course, it will lie somewhere in between these extremes. There are a number of different views concerning what constitutes a strong or weak correlation, but the leading criterion is:

o   The significance of this coefficient. If the level of significance is below .05 (p<.05), the correlation is significant and we can conclude that the two variables are related.

Regression analysis: Most of the time, you will be interested in the distinction between dependent and independent variables, and in the extent to which dependent variables are explained (or influenced) by these independent variables. Then, you will perform a regression analysis, which enables you to test a model like the following:

Typically , Y will be what you enter in the “dependent” box, and X1, X2 and X3 will be entered in the “independents” box. In a regression analysis, pay attention to the following criteria in the output:

o   (Adjusted) R-square. This tells you how much variance in the dependent variable is explained by the independents in your model. For instance, an R-square of .48 means that 48% of the variance in the dependent is explained by your model. There is some discussion whether you should look at the R-square itself or the Adjusted R-square, but since the latter is a more conservative estimate it is preferable to choose the Adjusted R-square.

o   F-value and significance of F-value. Here, the F-value tells you whether the proportion of variance explained by your model is significant. In other words, whether the (Adj) R-square is significant, if the model has enough explanatory power to be valuable. If the F-value is not significant, that means it makes no sense to continue your analysis and you have to design a different model.

o   Betas and significance of Betas. The Beta can be compared to the correlation coefficient, and tells you how strong the relationship between your independent and dependent variable are, and what direction it has (positive or negative). Typically, Beta values will lie between -1 and 1, and the most important thing here is whether the Beta value is significant (p<.05).

-          WHERE?

o   Analyze > Correlations > Bivariate

o   Analyze > Regression > Linear

Moderation & Mediation Analysis in SPSS

a.     analyze>descriptives>save as standardized values (select the independent and moderating variable)

b.     transform>compute (calculate the product of the 2 standardized variables)

c.      analyze > regression > linear (select your dependent variable, insert the independent and moderating variable in step 1, click next, and add the product in step 2)

d.     Is the best of the product significant? Then there is moderation.

Mediation

a.     Is there an association of the independent variable with the mediator? (analyze >regression > linear; independent variable is inserted as independent variable and mediator is added as dependent variable)

b.     Is there an association of the mediator with the dependent variable? (analyze > regression > linear; mediator is inserted as independent variable and the dependent variable is added as dependent variable)

c.      Is there an association of the independent variable with the dependent variable? (analyze > regression > linear; independent variable is inserted as independent variable and dependent variable is added as dependent variable)

d.     Does the association of independent and dependent variable reduce significantly (partial mediation) or disappear (full mediation) in case the mediator is added? (analyze à regression à linear; independent variable is inserted as independent variable and dependent variable is added as dependent variable in step 1; click next, and add the mediator in step 2)

More video tutorials on SPSS

For more information and video tutorials on SPSS go to SPSS student movies and view the following flash movies (these videos run more smoothly when you download them first onto your hard drive):

o  Entering Data
o  The Syntax Window
o  Transforming Data
o  Regression
o  One-Way Independent ANOVA

As a leader, whenever you delegate a task, you need to make it clear what level of authority you are conferring to others:

• Level 1: Do exactly what I have asked you to do. Don’t deviate from myinstructions. I have already researched the options and determined what I want you to do.

• Level 2: Research the topic and report back. We will discuss it, and then I will make the decision and tell you what I want you to do.

• Level 3: Research the topic, outline the options, and make a recommendation. Give me the pros and cons of each option, but tell me what you think we should do. If I agree with your decision, I will authorize you to move forward.

• Level 4: Make a decision and then tell me what you did. I trust you to do the research, make the best decision you can, and then keep me in the loop. I don’t want to be surprised by someone else.

• Level 5: Make whatever decision you think is best. No need to report back. I trust you completely. I know you will follow through. You have my full support.

The problem is that my mentee thought he was delegating at Level 2. The person on his team assumed he had given him Level 4. The whole problem could have been avoided by clarifying the expectations on the front end. If you’re not sure which level of delegation your boss meant, ask him to clarify.

Always make sure it’s clear to both parties which level of delegation is expected to avoid conflict. Then when you high potentials with some luck and passion (and probably some entrepreneurship) make your first millions, here are some tips on what not to do with the money.

I really enjoyed the process of the research as preparation for the final master thesis. The field of M&A presented to be a fascinating world! Enjoy the read or skip to the management matrix to find how you can best manage acquisition experience in the pre-formation given your level of current acquisition experience.

Managing the influence of previous M&A experience on potential synergies in the pre-formation process.

Introduction

While the intuitive expectation is that M&A experience would be positively related with M&A performance the literature shows mixed results (Haleblian et al., 2010; King et al, 2003) and frequently fails to positively relate acquisition experience to acquisition performance (Haleblian & Finkelstein, 1999). While some acquirers with acquisition habits successfully perform acquisitions to gain market power, it seems that generally acquirers fail to realize this potential from acquisition experience (Hayward, 2002). The academic literature on acquisition experience suggest different moderating influences on the possible relation between acquisition experience and firm performance. This makes theoretical integration and the applicability for managers difficult.

The acquisition process is moderated by many conditions that can influence the final acquisition performance (Haleblian et al.,2010). It is also suggested that there might be an existence of unidentified variables that may explain the significant variance in post-formation performance (King et al., 2003). These unidentified variables could have an influence on the effect of acquisition experience on performance and be the cause of the mixed research results.

I argue that the mixed results in previous acquisition experience research are due to the broad scope used. Most papers analyze the formation process as a whole without a clear distinction between pre- and post-acquisition process and those that focuses on the post-formation process and performance still shows mixed results due to the complexities and interdependent variables in the integration stage (Larsson & Finkelstein, 1999) and unidentified variables that influence the post-formation process (King et al., 2003).

Most of the existing literature on acquisition experience analyze the performance or success in the post-formation process, while the influence in the pre-formation process has been largely ignored. In this paper I answer the following research question: How does acquisition experience influence the potential synergy realization in the pre-formation process, and how can this be managed?

This paper looks at the influence of acquisition experience on the success in the pre-formation process and contributes by explaining how this can be managed in practice. The dependent success variable is not defined as performance, but as the potential synergy realization. By doing this the inconclusive influence of other variables mainly in the post-formation process can be excluded and with this new scope it’s possible to arrive at new insights on acquisition experience in this pre-formation process.

Where previous large-sample studies provide limited new insights into the factors that influence M&A outcomes (Healy et al., 1992) I use qualitative research to study the effect of acquisition experience in the pre-formation process in more detail. Applying the existing theories to the pre-formation process and combining it’s predictions with qualitative research from 12 interviews that were held with M&A consultants and managers with M&A experience about the pre-formation process.

This paper starts by analyzing the existing literature and potential moderators on the acquisition experience effect. Combined with the findings from the interviews a conceptual model is developed in which I argue that acquisition experience can be managed to realize higher synergy potential. This is connected further with finding from the interviews to develop a management matrix which managers can use to analyze the effects and the aspects of acquisition experience in the pre-formation process given their level of acquisition experience. Inexperienced acquirers can use the matrix to analyze opportunities on how to escape from the negative effects of low acquisition experience.

Theoretical background

Pre-formation

This paper focuses on the pre-formation part of a merger or acquisition. The pre-formation process starts from the first step of intent or research into an acquisition target till the point where the final contract is signed. After the signing of the contract the post-formation (integration) process starts.

Potential synergy realization

The M&A literature on acquisition experience presents a couple of ways to approach the dependent ‘success’ variable. The dependent variable in acquisition experience research is often approached as: acquisition performance (Heleblian & Finkelstein, 1999; Haywards, 2002), announcement returns (Haleblian & Finkelstein, 2002), or even as part of the performance of a whole acquisition program (Laamanen & Keil, 2008).

The existing M&A literature on acquisition experience often looks at the (stock) performance in the post-formation process. Whether it’s at day 0 at the announcement, half a year into the integration or final results of the post-formation process. Healy et al. (1992) argue that stock price performance studies are not able to determine the gains of an M&A or identify the sources of these gains. I argue that by focusing on the success measures of the pre- and post-formation stages independently, the sources of these gains can be identify better and that the influence of unidentified moderating variables (King et al., 2003) in the post-formation process can be left out. The success of the pre-formation process does not guarantee success in the post-formation process which is greatly dependent on drivers of post-formation integration (Epstein, 2004).

Figure 1. Integrative Merger & Integration model

In this paper the dependent ‘success’ variable in this pre-formation process is defined as the potential synergy realization. These potential synergies arise in the pre-formation planning. The potential synergy realization is comparible with the combination potential where post-formation process starts with and has a direct and non-direct effect on the final realized synergies (Larsson & Frinkelstein, 1999).

Organizational learning

To make predictions of the influence of acquisition experience in the pre-formation process a organization learning perspective is used to analyze the existing acquisition experience literature.

The organizational learning perspective explains how organizations learn form direct experience and even from experience of others. According to this perspective organizations learn by encoding history into their routines which in turn guide behavior. Experience is encode into conceptual frameworks and the likely hood these routines are used increases as they are associated with success (Levitt & March, 1988).

Acquisition experience

Haleblian & Finkelstein (1999) find that the effect of prior acquisition experience on the performance of acquisitions is U-shaped instead of linear and that it can be positive as well as negative. Using a behavioral learning theory from psychology they explain this effect. Firms start with a baseline at their first acquisition, but due inexperience make inappropriate generalizations of their acquisition experience at following dissimilar acquisition. Once firms gain sufficient acquisition experience they start to appropriately discriminate between acquisitions increasing performance again.

Laamanen & Keil (2008) suggest that acquisition experience has a more complex relationship with acquisition performance. From a acquisition program-level perspective they find that acquisition experience has a negative direct effect on acquisition performance, but a positive indirect moderation effect on the negative effects of high acquisition rates and variability of the rates. Acquisition programs can benefit from experience by learning which capabilities they have to manage an acquisition, the optimal number of firms to acquire, timing and the type of firms to acquire.

Other authors (Zello & Winter, 2002; Hayward, 2002) argue that experience alone is not sufficient and doesn’t ensure acquisition performance on its own. Zollo & Winter (2002) find no direct relation between experience and acquisition performance, but state that codification of experience leads to higher acquisition performance. Especially for inexperienced acquirers codification can moderate the negative effects of generalization due to high heterogeneity in task experience.

Hayward (2002) finds that prior acquisition performance is positively related with acquisition performance, if the target isn’t too similar or dissimilar to the previous acquisition and if it’s not temporally too close or distant from the previous acquisition. Experience per se is insufficient, but also necessary for acquisition learning. With an organizational learning perspective Hayward (2002) formulated that organizations must learn how to select the right acquisition and that this relates to the quality and not the quantity of the firm’s experience.

Although it seems intuitive that M&A experience would be positively related to M&A performance the literature shows mixed results. Acquisition experience is presented both as a independent variable with a positive and negative influence on performance as well as a moderator that moderates effects on performance (Haleblian et al., 2010). These unclear relations make managing acquisition experience to realize a positive effect difficult. I argue that these mixed results are due the broad scope, unidentified variables in the formation process as a whole and difficulty in measuring the influence on acquisition success with financial performance measures.

Overall the literature finds many interrelated variables and given the various circumstances acquisition experience could be managed to result in a direct, indirect or U-shaped positive effect.

Target similarity

The theory on acquisition experience suggests that target similarity is an important moderator that influences the effect of acquisition experience. This moderator fits with the organizational learning perspective.

The more similar a target is to the acquirers prior targets, the better the acquisition performs. Haleblian & Finkelstein (1999) find a positive relation of target similarity with acquisition performance. Hayward (2002) finds that acquisition performance is positively related with acquisitions that are not highly similar or dissimilar to the focal acquisition.

This effect is especially important for inexperienced firms that can make wrong generalizations of their acquisition experience due to high heterogeneity in task experience (Zollo & Winter , 2002). Target similarity especially helps inexperienced firms to moderate the negative effect of wrongly generalizing previous acquisition experience to unrelated current targets. While highly experienced firms are better able to discriminate between acquisitions.

Theoretical framework

Figure 2. Theoretical framework

Using an organizational learning perspective combined with the existing literature acquisition experience will be gained by trail-and-error and when successful, this experience is turned into routines of the organization and thus has a positive effect on the potential synergy realization.
Within this perspective acquisition experience is positively related to the ability to judge targets and estimate synergy expectations. Intuitively a higher level of acquisition experience leads to better and more careful pre-merger planning which creates these potential synergies. With experience its possible to identify better acquisition targets and manage the pre-formation process better than with less experience. Trough organizational learning the organization and its managers learn from M&A experience and become better at managing the pre-formation process. Without experience it will be hard for managers to realize high potential synergies. Learning seems to play an important role in realizing this positive effect.

This effect is moderated by target similarity. As target similarity increase the on the acquisition experience effect becomes more positive and increases this effect. Target similarity has the strongest moderating effect on firms with low acquisition experience.

Here target similar is the similarity to the previous target. This can also be targets that are similar to the firm, but from a organizational learning perspective I argue that similarity to the previous target and experience with these processes is important. Thus the concept of industry familiarity is approached more in a process way where experience is gained, than in a knowledge perspective of having knowledge of the target industry compared to the own industry.  Whether the target is similar to the firm or not doesn’t matter form a learning perspective.

Results

The findings from the interviews confirm the developed theoretical model on the influence of acquisition experience in the pre-formation process. A positive effect of acquisition experience was found, while problems that arise due to inexperience were also found in the interviews. Target similarity is also found to be related with acquisition experience and can be managed to stimulate its positive effect.

Importance of experience in the pre-formation process

The interviews indicate that acquisition experience is very important in the whole pre-formation process. The more experience the bigger the change to do everything right without making mistakes. Experience helps to oversee the processes and helps to know what to say and when. Firms with experience indicate that they use this information to avoid failures. Without acquisition experience it would be hard to realize potential synergies. Experience is so important in the pre-formation process that some indicated the need to hire and external advisor to access acquisition experience.

Level of acquisition experience

Acquisition experience in the pre-formation process is managed in different ways depending on the level of acquisition experience.

High levels of acquisition experience are used by managers in the pre-formation process to be realistic about the potential synergies and in which areas these are possible. Firms with high levels of acquisition experience create and use benchmarks and detailed planning to estimate the potential synergies. Another important factor found in the interviews is speed. Acquisition experience helps to increase speed by getting to negotiations quicker and the ability to accesses agreements.
The interviews show that managers create benchmarks and checklists based on their experience to make the pre-formation process more efficient and to estimate the potential synergies. Over time these firms with many previous acquisitions and high levels of acquisition experience develop a rigid process to manage and benefit from this experience.

Low levels of acquisition experience are not familiar with all the necessary processes which will make the pre-formation process long and difficult. With higher levels of experience they would be able to go through the process quicker and know when to get to making the deal.

Firms who lack acquisition experience try to access experience from outside the company. An external advisor or consultancy is approached to advice during the pre-formation process or to do certain parts of the process where the firm lacks experience. The processes of Due Diligence is often conducted by external consultancies.

Target similarity

Experience with a similar type of target increases the efficiencies and potential synergies that can be realized in the pre-formation process. Target similarity makes this process easier, because the departments and specific methods that are evolved are familiar, thus enabling the use of previous experience. Many of the steps in the pre-formation process are the same and some, for example industry evaluation, don’t need to be done again. Experience in evaluating the value of assets for similar firms can also save times and money spend in the pre-formation.

The interviews also indicate that the influence of similarity is low for firms with high levels of acquisition experience, because of the strict acquisition process that was developed to prevent wrong generalizations.

Management matrix

The results of the different levels of both acquisition experience and target similarity and how these are managed are translated into a management matrix.

Figure 3. Acquisition experience management model

This matrix can be used by managers in the pre-formation process to analyze the effects of acquisition experience given their level of experience. Firms that find negative effects can escape these negative effects by increasing target similarity or by using the suggested management processes. Inexperienced firms can learn from the management processes that experienced firms used to reap the benefits of acquisition experience.

Firms with low acquisition experience see little or even a negative effect of experience due to wrong generalizations. Without accessing external experience in the form fo an advisor or consultancy it will be hard to realize synergies. By increasing target similarity this negative effect can be moderated.

Firms with high acquisition experience benefit the most form acquisition experience and trough learning developed processes that enables them to increase efficiency and speed in the pre-formation process. Target similarity mainly effects firms with low acquisition experience, but can also help experienced firms to increase their pre-formation process efficiencies.

Conclusion

By focusing the scope on the pre-formation process and applying a organization learning perspective combined with the existing literature on acquisition experience I was able to develop a theoretical framework that predicted the positive effect of acquisition experience on potential synergy realization. This effect is indeed found to be moderated by target similarity. In the interviews I found empirical evidence of the positive effect of acquisition experience, the importance and how the acquisition experience gets managed to benefit from. From a organizational learning rationale I argue that low levels of experience that are not moderated by target similarity can experience a negative effect that becomes positive as experience increases.

Acquisition experience is found to be an important aspect in the pre-formation process, which can be managed. Increasing acquisition experience through organizational learning has a increasing positive effect on the potential synergy realization in the pre-formation process. Firms that lack acquisition experience will have more difficulties to realize potential synergies and more often access external acquisition experience by hiring a consultancy for more parts of the process. Firms with higher levels of acquisition experience were found to create processes that increase the efficiency during the pre-formation process and their ability to estimate potential synergies.

Target similarity moderates the positive effects of acquisition experience mostly for firms with low levels of acquisition experience. These firms can especially benefit from target similarity where some parts of the pre-formation process can be similar and can help them to increase efficiency.

The effects of acquisition experience and target similarity for each high and low level used to develop an acquisition experience management model. This model can be used by managers to escape from the negative effects of low acquisition experience or to find the effects and management methods that can be used given their level of experience and similarity of their current target. Firms with low levels of experience can escape these negative effects by increasing target similarity. For each quadrant a set of management practices is suggested that firms were found to use to reap the most benefits of their acquisition experience.

References

Epstein M. J., 2004, The drivers of success in post-merger integration, Organizational Dynamics, Volume: 33, Issue: 2, Pages: 174-189

King D. R. , Dalton R., Daily C. & Covin J., 2004, Meta-analyses of post-acquisition performance: indications of unidentified moderators, Strategic Management Journal, Volume 25, Issue 2, pages 187–200

Laamanen T. & Keil T., 2008, Performance of serial acquirers: toward an acquisition program perspective, Strategic Management Journal, Volume 29, Issue 6, pages 663–672

Larsson R. & Finkelstein S., 1999, Integrating Strategic, Organizational, and Human Resource Perspectives on Mergers and Acquisitions: A Case Survey of Synergy Realization, Organization Science, Vol. 10, No. 1, pp. 1-26

Levitt B. & March J.G., 1988, Organizational learning, Annual Review of Sociology, vol 14. pp 319-340

Moellera S.B., Schlingemannb F.P.  & Stulz R. M., 2004, Firm size and the gains from acquisitions, Journal of Financial Economics, Volume 73, Issue 2, Pages 201-228

Haleblian J., Devers C. E., McNamara G., Carpenter M. A. & Davison R. B., 2009, Taking stock of what we know about mergers and acquisitions: A review and research agenda, Journal of Management, vol. 35 no. 3 469-502

Haleblian J., Finkelstein S. 1999, The Influence of Organizational Acquisition Experience on Acquisition Performance:  A Behavioral Learning Perspective, Administrative Science Quarterly, Vol. 44

Hayward M. L. A., 2002, When do firms learn from their acquisition experience? Evidence from 1990 to 1995, Strategic Management Journal, Volume 23, Issue 1, pages 21–39

Healy P. M., Palepu P. G. & Ruback R. S., 1992, Does corporate performance improve after mergers? Journal of Financial Economics, Volume 31, Issue 2, Pages 135-175

Zollo M. & Winter S. G., 2002, Deliberate learning and the evolution of dynamic capabilities, Organization science, Volume 13 Issue 3,

By publishing my thesis in parts on my blog i received much feedback in the reactions and on twitter. Special thanks to Michiel Hartman for pointing out that the evolution of web 1.0 to 2.0 hasn’t been a linear process.

You can download the ‘The alignment of web 2.0 and social media with business strategy’ (van der Weel, A. T. ,2009) pdf here.

For those who want to read the short summery and conclusions I included them here at the end of the blogpost. I also added the references for those who are interested in finding more academic research papers on social media and business strategy.

Research questions

Corporations trying to adopt and use web 2.0 and social media applications in their business, raises the question of how organizations can use these in extend to their strategies.

• How should web 2.0 and social media be approached and how can organizations align these web 2.0 and social media developments with their organization strategy?

To answer this question the following sub questions need to be answered:

• What is web 2.0 and social media and what are good definitions?
• How can social media be approached and used by organizations?
• How can social media be aligned with the business strategy of organizations?

Short summary

I expanded existing academic theory on ‘Possible uses of the World-Wide Web for business’ by adding customer service as the main new opportunity offered by web 2.0 and social media.

My literature research identified two frameworks that can be used to analyze web 2.0 and social media. One is the ‘Technology-Centric view of IT in Business’ (Dhar & Sundararajan, 2007), which presents technological invariants and consequences in business. This framework can be used for fundamental analysis of the building blocks and consequences of web 2.0 and social media.

The ‘Strategic alignment model’ (Henderson & Venkatraman, 1993) indicates the importance of a functional and strategic fit between business and IT. Together with the the ‘Value Disciplines’ framework (Treacy & Wiersema, 1993) these frameworks can be used to align organization business strategy with social media and web 2.0.

The Value Discipline that express the business focus on organization or department level can be used to guide the focus of the social media strategy. While the thesis mainly looks at the business strategy of the organization as a whole, it can also be used for departments to align their social media strategy.

In the end the researched frameworks come together to present my ‘social media governance framework’ which looks at the internal and external dimensions and the usage channel of social media in the organization. It can be used to align new social media projects with business strategy or to analyze the strategic fit of current social media projects in the organization by placing them in the matrix.

Conclusions

Web 2.0 was identified after the dot-com crash and is a collection of technologies, services and platforms. Key to business in web 2.0 is the ‘harnessing of collective intelligence’ often also called the ‘power of the crowd’. Social media can be defined as ‘the collective goods produced through computer-mediated action on web 2.0 services and platforms’. When focusing on the business uses social media encompasses these services and platforms that can be used by organizations. Social media and web 2.0 are greatly driven by modularity and result in the creation of large IT platforms and computer-mediated spaces.

Like internet, social media can be used for: Publicity, marketing and advertising, direct online selling, research and development, communication, collaboration and customer service. E-services helped identify the customer service path as a new business use after the dot-com crash and rise of web 2.0. Enterprise use of social media mostly focuses on reaping benefits from internal communication and collaboration cross traditional organizational hierarchies. Social media can be approached from an inward(internal) e-commerce perspective or from an outward(external) e-service perspective e-strategies depend on the approach.

For investments in social media to be effective corporations need to have an alignment between social media (IT) and business strategy. Also the strategic fit between the internal and external IT domain needs to be considered. The social media governance framework I present helps identify how different types of organizations should deploy social media applications depending on the purpose and business strategy in the internal or external domain. Alignment between the social media (IT) and business strategy occurs by using the value disciplines of an organization to formulate social media strategies. I argue that operational excellence organizations should have a focus on internal use of social media and that customer intimacy organizations should have a focus on the external use of social media. With the growing importance of social media in organizations, social media should become part of IT governance in organizations top management to support the alignment.

References

• Anderson, Paul (2007). What is Web 2.0? Ideas, technologies and implications for education. JISC Technology and Standards Watch, Feb.
• Brzozowski, Michael J., Sandholm, Thomas and Hogg, Tad (2009). Effects of Feedback and Peer Pressure on Contributions to Enterprise Social Media. GROUP‟09, May 10–13, Sanibel Island, Florida, USA.
• Cockburn, C. and Wilson, T. D (1996). Business Use of the World-WideWeb. Vol. 16, No. 2, pp. 83-102.
• Dhar, Vasant and Sundararajan, Arun (2007). Information Technologies in Business: A blueprint for education and research. Information systems research, vol 18, No. 2, pp. 125-141.
• Eichen, Marc (2006). Value disciplines: a lens for successful decision making in IT. EDUCAUSE Quarterly, Vol. 29, No. 2. pp. 32-39.
• Gartner research (2008). The Enterprise Social Software Market Continues to Expand. 30 May.
• Gurbaxani, Vijay and Whang, Seungjin (1991). The Impact of Information Systems on Organizations and Markets. Communications of the ACM, January Vo1.34, No.1.
• Henderson, J.C. and Venkatraman, N. (1999). Strategic alignment: Leveraging information technology for transforming organizations. IBM systems Journal 38, 2/3 pg. 472.
• Lai, Vincent S. and Wong, Bo K (2005). Business types, e-strategies, and performance. Communications of the ACM, May Vol. 48, No. 5
• O’Reilly, Tim (2007). What Is Web 2.0: Design Patterns and Business Models for the Next Generation of Software Communications & Strategies no. 65, 1st quarter.
• Hoegg, Roman, Meckel, Miriam, Stanoevska-Slabeva, Katarina and Martignoni, Robert (2006). Overview of business models for Web 2.0 communities, Proceedings of GeNeMe: 23-37
• Kochan Thomas A., Useem, Michael (1992). Transforming organizations. Oxford University Press US http://books.google.nl/books?id=qU96bV4OtdgC.
• Raghupathi, W. RP (2007). Corporate governance of IT: A framework for development. Communications of the ACM , August Vol. 50, No. 8.
• Rai, Arun, Patnayakuni, Ravi and Patnayakuni, Nainika (1997). Technology Investment and Business Performance. Communications of the ACM, July Vol. 40, No. 7.
• Rust, Roland T. and Kannan, P.K. (2003). E-service: a new paradigm for business in the electronic environment. Communications of the ACM, June Vol. 46, No. 6
• Smith, Marc, Barash, Vladimir, Getoor, Lise and Lauw, Hady W. (2008). Leveraging Social Context for Searching Social Media. SSM‟08, October 30, Napa Valley, California, USA.
• Tracy, M. and Wiersema, F. (1993). Customer intimacy and other value disciplines. Harvard Business Review 71 (1), Jan/Feb, pp. 84-93
• Valacich, Joseph and Schneider, Christoph (2009). Chapter 6 Enhancing Collaboration Using Web 2.0 in Information Systems Today: Managing the Digital World, Prentice Hall; 4 edition (March 13)

Internal and external business approach to the electronic environment

The strategic alignment model states that strategy must be addressed in an Internal and external domain. The research that follows on electronic strategies and business types also indicate organizations can have an internal or external focus.

E-service: a new paradigm for business in the electronic environment

Rust & Kannan (2003) argue that the traditional path of e-commerce has largely failed after the dot-com crash, and that organizations must learn to embrace the e-service paradigm that can offer new forms of competitive advantage. Putting the firm in a position attending to the needs of the customer by providing software service in addition to selling products

The transformation of physical products to service products is enabled and hasted by electronic networks. For firms to garner long-term customer relationships they must take full advantage of the e-service opportunities that these electronic networks can offer. They predict that product-centered orientated firms that resist the call of the customers for control are not likely to survive in this electronic environment and give the example of record labels.

The traditional path is focused on automation and efficiency to reduce costs. While the e-service path is focused on enhancing service and building profitable customer relationships to increase revenues. There is a shift form focusing on technology and systems towards focusing on understanding the customer. While the new path offers new forms of competitive advantage both can still be used by organizations to perform successfully.

The electronic environment enables both this inward and outward-looking view of e-commerce. The e-service paradigm identifies a new use of internet for improved customer satisfaction as opposed to increased efficiency and productivity. The e-service paradigm takes advantage of the nature the online environment with its flows of information to learn about customers, communicate and engage in long-term relationships to build customer equity (Rust & Kannan, 2003). E-services identify customer service as an important new approach of businesses in electronic environments.

According to Rust Kannan (2003): “Dell Computers is a good example of how a firm selling products in an increasingly commodity market can follow an e-service orientation to build its customer equity.“ Organizations as IBM, HP and Sun are also undergoing this shift and increasingly focus on their services as prime revenue source.

Business types, e-strategies, and performance

After the dot-com crash IT developments continued shaping towards web 2.0 and new services emerged (Hoegg et al. 2006) creating new business opportunities (Rust & Kannan, 2003)  and new e-strategies emerged. Lai & Wong (2005) mention that the companies that survived the dotcom crash needed to device innovative e-strategies and restructure around new business models. After reengineering efforts some companies recuperated from the debacle.

In their research they look at companies after the EC crash and investigate the influence of different business types(B2B & B2C) and non-EC on the company performance. Also the e-strategies from the different companies are identified and their effectiveness correlated with the company performance.

The results indicate a moderating the relationship between business type and e-strategy performance.

Findings indicate that many EC companies used four different types of e-strategies. Savings-related strategies were most effective for B2B and B2C companies, while marketing-related strategies were only effective for non-EC companies. The business type that benefited the most from the e-strategies were B2B companies and also performed better than their B2C counterparts.

Conclusion: How to approach social media

E-strategies further help identify how organizations approach the electronic environment and which strategies they use. The four main types of e-strategies are identified as: savings-related, structure-related, policy-related and marketing-related. These identified strategies can also be subdivided between internal and external strategies. Savings, structure and policy-related are inward focused strategies while marketing-related strategy is focused outwards.

Rust and Kannan (2003) identify two different paths of e-commerce. The traditional path focused on automation and efficiency to reduce costs and the e-service path focused on enhancing service and building profitable customer relationships to increase revenues (Rust & Kannan, 2003). The traditional e-commerce path and e-service path help identify two approaches of businesses to the electronic environment. One focused inwards on processes and the other focused outwards on customer satisfaction. Organizations can adopt an internal as well as an external focus.

Both papers indicate the existence of an internal and external focus for organization strategies and are in line with the strategic alignment model that was presented and help identify how different organizations can use social media and web 2.0 in their (electronic) strategies.

I argue the same strategies can be used when formulating strategies for the use of social media in organizations, because social media operates in the same electronic environment on web 2.0 services and platforms. Also the e-strategies theory can be connected to e-commerce or e-service paths by making a distinction between internal and external focus.

Functions of web 2.0

Possible uses of the World-Wide Web for business

Having answered what web 2.0 and social media is and developed definitions for both, now the possible use of social media by organizations can be researched. Cockburn and Wilson (1996) present a list of applications for which businesses are using the WWW. While their paper was written at the beginning of the internet era, it can still be used to identify the purposes and goals of businesses on the internet. They identified the following application areas:

Publicity, marketing and advertising:  the WWW appears to be an ideal medium for businesses to promote themselves and their products. Gaining access to millions of people can be achieved by a small fraction of the costs of conventional methods.

Direct online selling: can revolutionize the way in which people shop. Virtual shops and catalogues are available on the web where customers can directly buy products.

Research and development: especially companies involved in research and development can use the internet as an additional resource for collecting information. Many databases are available and discussion boards that can be searched and queried for information and data.

Communication: use of low-cost electronic mail(and other ways of online communication )that allows many companies to link together and communicate internal and external  in an easy and fast way.

Collaboration: fast and easy forming of links and collaboration over the internet instead of using private (network) links.

After the dot-com crash new web business characteristics were identified as web 2.0 (O’Reilly, 2007) and businesses had to understand the new rules for success on that new platform (Valacich & Schneider, 2009). The survey was done in 1996 before the dot-com crash and new developments have led to new approaches and use of the internet. Modern web 2.0 business uses like e-commerce can be seen as part of Direct online selling. Crowd sourcing that makes use of the collective intelligence of web 2.0 (O’Reilly, 2007) can be seen as part of Research and development and Collaboration.

Internal enterprise use of social media focuses reaping the benefits from internal collaboration and communication and makes use of web 2.0 services to achieve this. The free broadcasting platform that social media offers, helps to circumvent traditional organizational hierarchies (Brzozowski et al. 2009).

While the list of applications for which businesses use the internet still is valid, I argue that one business application is missing that was identified after the dot-com crash. Customer service is the main new business application that originated from the paradigm shift after the dot-com crash (Rust & Kannan, 2003) and should be added to the list. Zappos.com is an example of a company that mainly focuses on using internet to offer customer service, with the use of a blog, chat and other messaging services. These are used as a support function on their e-commerce services that are used for direct online selling.

Conclusion: How organizations can use social media

The possible uses of the Internet for business were identified by Cockburn and Wilson (1996) in their survey that presented a list of applications for which businesses were using the internet. I identified one main application that was missing and updated the list. The business uses of internet are: Publicity, marketing and advertising, direct online selling, research and development, communication, collaboration and customer service.

The list of possible business applications of the internet helps identify the use of social media for organizations. I argue that these applications can also be applied to the use of social media that operates on top of web 2.0 services and platforms. Web 2.0 and social media that operates on top of it offer new opportunities, but I argue that the same goals on the web remain. One of the new opportunities that arrived with the rise of web 2.0 and e-services is customer service that can be a goal of businesses on the internet, and was added to the list.

These possible uses of the internet overlap with the possible uses of social media. Only now web 2.0 and social media has really enabled the possibilities to achieve these uses and goals on the internet while at the start of the internet era the possibilities were still limited. These uses will be important for the model that is presented later on in this paper.

Aligning business and IT strategy

Now that we have definitions of web 2.0 and social media and the importance of them for organizations we continue the research on how organizations can approach these and align them with their organization strategy.

Organizations can adopt an internal or external focus, for their business strategy as well as their IT strategy. This chapter will present evidence that IT, electronic and social media strategies should also be formulated in internal and external dimensions and how these strategies should be governed by organizations.

The strategic alignment model

Strategic alignment model, Oxford University Press US (1992)

IT strategy should be articulated in terms of an external domain and an internal domain. Where the external domain focuses on the position of the firm in the IT marketplace and the internal domain focuses on how the internal Information Systems should be managed. To acquire an adequate fit that delivers benefits to IT investments a strategic fit between internal and external domains is needed. Benefits can be realized by finding a fit between internal and external IT applications and platforms.

Between IT strategy and business strategy there is also a need for functional integration that takes note of the impacts each has on another (Henderson et al. 1993). This way, more value can be realized from investments in IT as they take note of the business strategy and goals the organization has. IT effects on business performance varies across organizations, because of the ability to achieve a link between business and IT strategy (Rai et al. 1997).

The need for strategic alignment of IT

IT has evolved from an administrative role towards a strategic role that can support and shape business strategies. Yet sometimes there seems to be an inability to realize value form IT investments. Henderson et al.(1993) argue that this is due a lack of alignment between business and IT strategies in organizations.

Trying to achieve strategic fit between the dynamic internal support structure and the external product-market is a continuous process of adoption and change. Exploiting IT functionality on a continuous basis can deliver sustained competitive advantage. Organizations try leveraging their IT capabilities to differentiate operations from their competitors and use these capabilities to shape and support their business strategies. This underlines the importance and value of aligning both strategies in organizations.

Technology Investment and Business Performance

Rai et al. (1997) argue that when calculating the return on corporate IT investments focus must lie on the links between IT, business strategy and competitive context.

While IT likely improves organizational efficiency the effect on business performance varies across organizations, because of the firm’s management processes links with IT strategy. This emphasizes the need for linkage between IT and business strategy.

IT investments are often not well measurable with ROA or ROE. This paper suggest to break down IT investments, not treating as a whole entity and following an justification process that considers specific objectives of the proposed investments. For example investments aimed at reducing labor costs can be justified on the basis of cost savings

Corporate governance of IT

Raghupathi (2007) recognizes the value of internal and external strategic fit (Henderson et al.1993) and argues that modern IT governance should formulate strategies according to this model.

IT Governance can be defined as: “The organizational capacity to control the formation and implementation of IT strategy and provide direction to achieve competitive advantages for the corporation”. IT is critical for supporting and enabling enterprise goals. Effective ITG can generate real business benefits like reputation, trust, product leadership, time-to-market and reduced costs. These benefits all increase stakeholder value.

This emphasized the alignment of IT objective with business strategy. IT governance cannot be an isolated activity and must be part of top management. IT Governance is changing: ”Boards of directors are beginning to look beyond the accounting roots of IT governance toward the risk of legal liability and harm to product brand and corporate reputation.”

Conclusion

Inability to realize value from IT investments is due to lack of alignment between business and IT strategies in organizations (Henderson et al.1993).

There is a need for strategic fit between internal and external domain of IT and a functional integration between business and IT strategy (Henderson et al.1993). To achieve this alignment IT governance cannot be an isolated activity and must be part of top management (Raghupathi, 2007). Modern IT governance should formulate strategies according to this model that recognized the value of internal and external strategic fit (Raghupathi, 2007).

I argue that social media strategy should be aligned with the business strategy of organization to achieve successful investments. With the growth of social media importance in organizations it should become part of IT governance. Where the ”Boards of directors are beginning to look beyond the accounting roots of IT governance toward the risk of legal liability and harm to product brand and corporate reputation (Raghupathi, 2007).”

Organization strategy formulated in value disciplines

Treacy and Wiersema(1993) presented the value disciplines model that describes three value disciplines that can help define the main focus of an organization’s business strategy, helping the organization to make strategic decisions. Choosing one will shape strategy and operational decisions in a company. These value disciplines are guidelines for organization strategy and in order to be competitive organizations need to maintain an acceptable level on all three disciplines while excelling in one. The three value disciplines are:

Operational excellence:  Aims at offering the best total cost. Optimizing internal and external processes to minimize costs. The focus in the organization is on standardization and streamlining of operations, efficiency and low total cost. Most large international corporations like McDonald’s, Wal-Mart and Dell focus on this discipline. (Marc Eichen, 2006)

Product leadership:  Aims at offering the best product or solution. The focus in the organization is on R&D, design and innovation. Organization structure and culture need to be flexible to stay ahead of competition and offer cutting-edge solutions to customers.

Customer intimacy: Aims at offering the best solution and focus on customers to maintain long-term relations and growth. Continuously tailoring and shaping products and services to fit customer needs. Organization structure needs to be flexible, close to the customer and solving the customer’s problem has to be put above all.

Marc Eichen (2006) argues in his article “Value disciplines: a lens for successful decision making in IT” that the value disciplines are a good method for IT strategy decisions to be aligned with the institutional goals of organizations.

Conclusion: Value disciplines: a lens for successful decision making in IT

Formulating organization strategy in terms of choosing one value disciplines gives and clear view on the business strategy of an organization. Having this clear definition helps communicating the strategy to the rest of the organization.

Operational excellence, product leadership and Customer intimacy can all be used to formulate the goals of IT strategy and shape strategic decisions. I argue they should be used by organizations as a starting point from which to formulate their social media strategy. This way the social media strategy will have a basis that is aligned with the business strategy of the organization.

Internal enterprise use of social media.

The social aspects of social media that allow the collecting and sharing of collective intelligence among the social media platforms users can be used by organizations to internally collect, retain and share information. The web 2.0 structure and technologies can also be used for easier communication and collaboration in organizations.

Brzozowski et al. (2009) write about the internal use of social media at Hewlett-Packard (HP). Social media provides a free broadcast platform that allows authors to circumvent traditional organizational hierarchies and reach organizationally distant readers. Unlike email that is targeted to specific recipients.

HP offers all employees a variety of social media services used for internal collaboration and communication. Internal blogs for example can facilitate internal collaboration and knowledge sharing and aim at the benefits of lightweight informal collaboration among employees.

To reap the benefits of internal social media usage managers should be stimulated to ‘leed by example’. For venues that imply discussion (e.g. blogs, comments, forums) external validation from managers is more important to the users than in venues of archives (e.g. links, wikis). Culture and organization structure also influence the internal support to use social media.

Analyzing the building blocks of web 2.0 and social media

Organization theory also indicates the importance of technologies and their consequences on organizations. Dhar & Sundararajan (2007) argue that the past forty years certain principles in IT can be recognized that remain constant. These invariants can be used to interpret the past and make predictions about information technologies in the future. They present a model where in the influence of these technological invariants and the consequences on IT in Business are explained. These invariants will be used to analyze web 2.0. The consequences on IT that are found seem to be in line with the technological trends we see in web 2.0.

Technological invariants

The first technological invariant is digital representation, the visualization of things as information and in particular digitally represented information. Examples are: a bank balance, music, our voice or video can all represented as digital information. This digitalization allows for new possibilities in the use and transport of information.

The second invariant is computing power. This is: “the long-term exponential growth of hardware power, broadband, storage and the miniaturization of IT devices”. Moore’s law, which states that the processing power doubles each six months, can explain this growth in computing power and has proven to be accurate. Computing power has grown, become cheaper and software has made it more reliable.

The last invariant is modularity, this is the sustained increase in programmability of IT systems in a modular way. This allows aggregated complexity to be easier integrated into existing standardized software platforms. This allows existing IT systems to add new functionality and usability with just modular additions to the software. This way Modularity fundamentally provides power to the first two invariants by making these possible and easier to achieve.

Digital representation is the technological invariant that has enabled many of the web 2.0 services to exist and grow with further digital representation of information. Blogs and wikis contain text, pictures, sounds and videos and increasingly more data and information that is made possible by digital representation of this information (Dhar & Sundararajan, 2007).

Computing power has increased and become cheaper (Dhar & Sundararajan, 2007) making internet publishing on blogs, wikis and other services fast, reliable and cheap. Barriers that might have existed in broadband for the streaming of video for example have been overcome by this continuously increase in computing power over the past 40 years.

Modularity drives the flexibility of web 2.0 allowing new functionalities and usability to be added to existing systems. Existing technologies on web 2.0 platforms are often updated enabling new functionalities. Gmail labs from Google and new functionalities in video’s on Youtube are examples of this. Widgets on blog services and widgets/apps on mobile phones also enable publishers to aggregate complexity trough modularity and offer users new functionality and usability trough updates and releases of widgets.

These three invariants are clearly identifiable in web 2.0 and contribute to the three consequences in the model.

Consequences in business

These three technological invariants form the building blocks to recognize the consequences of IT developments in business. Dhar & Sundararajan (2007) recognize three business consequences of these invariants. Digital representation together with the growth of computing power and communication power facilitate the separation of information from a growing number of artifacts. An example is the music CD, where the digital distribution of mp3′s only became feasible once there were internet connections fast enough to transfer the data.

This separation of information from its artifacts can alter the fundamental economics of an industry, making their products become information goods. The economics and production of information goods differ from tangible goods and will have many consequences for the way business operates once this separation starts to plays a role in the company’s sector. The music industry is one of the greatest examples of this and had to change traditional business models to still make profit in the digital music age.

The second consequence is the growth in computing hardware power and the ability of software to be layered in a modular way. This allows for IT infrastructures to become larger, more powerful and more accessible. Supply chain management software platforms and on-demand search platforms like Google are an example of this. Modularity results in functionality adopted by early innovators to be incrementally integrated into these powerful and shared infrastructure platforms.

The third consequence is a growth in society of the importance and variety of  IT mediated spaces of interaction. The difference between Technology-mediated spaces and spaces in the physical world is that technology mediated spaces are shaped continuously by the participants, where as real-life spaces are developed and launched in less continuous form. Digital representation is key in facilitating exchanges of information in these spaces. Computing power supports this by allowing the built of complex Technology-mediated interfaces and Software modularity enables the evolvement of spaces and build of new ones with little effort.

The first consequence ‘information separates form its artifacts’ in some industries has led to products to become information goods. In combination with electronic networks this has enabled and hasten the transformation of physical products to service products (Rust & Kannan, 2003), fundamentally changing economics and production of businesses in industries that are affected. In the music industry this has had great consequences. On the internet we see iTunes and Hulu as a response from the music and film industry to adapt to these changes and create new business models.

The second consequence, shared IT platforms of growing functionality, where IT infrastructures become larger, more powerful and more accessible. An on-demand search platform like Google is an example of this. These large accessible IT platforms can create opportunities and threats for companies which need to be addressed in corporate strategy.

The third consequence, the growth in importance of technology-mediated spaces and interfaces. Digital representation enables exchanges of information in these spaces and is what happens on blogs, wiki’s and other web 2.0 services. These exchanges are mediated in services and spaces that are found on IT and web 2.0 platforms. This is resembles what we see in social media spaces where: “collective goods are produced through computer-mediated collective action”(Smith et al. 2008). And these exchanges arise on web 2.0 services and platforms.

I argue that the third consequence is largely connected to the second consequence on the web. The technology-mediated spaces can be found in the social media part of web 2.0 that operates on large shared IT platforms.

Conclusion

The technological invariants and consequences of IT in business can be used to analyze the building blocks of web 2.0 technologies and the consequences of web 2.0 on IT in organizations. Web 2.0 is greatly driven by modularity and result in the creation of large IT platforms and computer-mediated spaces. Analyzing these IT developments in business has show that web 2.0 technologies are important for organizations.

Here is the first part of a serie of blogposts where I present the the research and findings of my Social Media & Business thesis. I hope you’ll comment and share your views on the material. In the end I will make a pdf available and we might even have updated sections based on comments/discussions!

Introduction

We are at the point of new developments in IT and business in the form of social software and social media applications. Many organizations and researchers have begun experimenting with the internal use of social software in the workplace (Brzozowski et al. 2009). The use of these technologies is quickly maturing and moving to enterprise-level projects and platforms and the social software marketplace is now starting to attract large vendors such as Google, IBM and Microsoft (Gartner research, 2008).

The goal of this research is to develop a model that allows web 2.0 and social media to be aligned with organization strategy. Reason for this is that aligning the business and IT strategies in organizations helps realizing more effective investments (Henderson et al.1993). These theories are analyzed in this paper and come together in the model that will be presented at the end.

Problem statement

Corporations trying to adopt and use web 2.0 and social media applications in their business, raises the question of how organizations can use these in extend to their strategies.

• How should web 2.0 and social media be approached and how can organizations align these web 2.0 and social media developments with their organization strategy?

To answer this question the following sub questions need to be answered:

• What is web 2.0 and social media and what are good definitions?
• How can social media be approached and used by organizations?
• How can social media be aligned with the business strategy of organizations?

Web 2.0 and social media theory

To get a clear definition of what web 2.0 and social media is and how organizations can use these, first web 2.0 will be researched. At the end of this chapter a clear definition of web 2.0 and social media is given and how they are connected.

Historical perspective of web 2.0, the dot-com bubble

After the burst of the dot-com bubble in 2001, it became clear that organizations that survived the crash had certain web business characteristics in common that were later identified as web2.0. (O’Reilly, 2007)

O’Reilly’s definition of web2.0 in 2006 is the following: “The business revolution in the computer industry caused by the move to the internet as a platform and an attempt to understand the rules for success on that new platform” (Valacich & Schneider, 2009). This indicates a shift in thinking about internet as a new platform. Web 2.0 is not only a collection of technologies but also a way of approaching these new technology applications to create successful business model.

The following list was created by O’Reilly when analyzing which applications are thought of as web2.0.

From an internet business perspective key to web 2.0 is: “The embracing of harnessing collective intelligence”. The new technologies and use of the web to allow a collective intelligence to be formed and created online. Businesses who succeed in embracing this can use it to their advantage.

According to O’Reilly (2007) internet businesses need to embrace this as a core competence and understand that: “Network effects from user contributions are the key to market dominance in the web 2.0 era”. This stresses even more the need for companies -especially internet business related- to understand this shift towards web 2.0 and the changes that it has brought.

Definition of web 2.0

While O’Reilly’s paper mainly focuses on the changes after the dot-com bubble for internet businesses it helped identify the general business aspect of web 2.0 as the ‘harnessing of collective intelligence’. It is hard to have a clear definition of a concept like web 2.0, because it doesn’t have clear boundaries (O’Reilly, 2007) and web 2.0 cannot be reduced to one principle (Hoegg et al. 2006).

Web 2.0 technologies can be used to develop different web 2.0 services and platforms. These web 2.0 services include: Blogs, Wikis, Podcasts, Social Networks and Social Bookmarking. Technologies like AJAX, API’s and RSS have made these new web 2.0 services possible and feasible ( Hoegg et al. 2006) .

Anderson(2007) presents a list of principles that he sees as key ideas that help define web 2.0. These key principles are in line with O’Reilly’s ‘collective intelligence’ definition and add to the definition of web 2.0 not only being a collection of technologies.

All these key principles offer new possibilities for communication, collaboration and business. The key idea of openness refers to the social philosophy of web 2.0 and data on an epic scale refers to the amounts of data we produce electronically. Some argue that maximizing the collective intelligence of the participants is fundamental to web 2.0 (Hoegg et al.2006). Web 2.0 isn’t just only about technological aspects, but also about social aspects like collective intelligence, communication and collaboration.

Definition of social media

From a sociological perspective, social media can be described as “collective goods produced through computer-mediated collective action”. An example is Wikipedia, where the collective goods are articles, and the collective action is the co-editing process of article writing (Smith et al. 2008). These goods are produced and shared on web 2.0 computer-mediated platforms.

Social media platforms offer valuable high quality content that is embedded in socially constructed repositories and the structure of these content collections is different from the web 1.0 structure (Smith et al. 2008). Social media uses the possibilities of the web 2.0 structure to enable the social aspect of collaboration, communication, media sharing and more.

Conclusion: Technology, services and platform aspects of web 2.0

Web 2.0 is not just a collection of technologies, but is a broader concept where technologies, services and platforms come together (Hoegg et al. 2006). To get a clear view of what web 2.0 and social media is and how these affect organizations a distinction is made between the different aspects of web 2.0.

Web 2.0 is a combination of technologies, services and platforms. For organizations to better understand web 2.0 and social media we make a distinction between three aspects of web 2.0. First we have web 2.0 technologies like AJAX, API’s and RSS. These enable web 2.0 services like Blogs, Wikis and Podcasts. These services come together on web 2.0 platforms like Facebook (social networks), Google, Blogger and Twitter. These platforms also allow new applications to be created on top of them like crowd sourcing, viral marketing campaigns and real-time information. On this platform aspect of web 2.0 is where social networks are found and where Social Media operates.

I argue that Social media can be identified in web 2.0 services and platforms and thus overlaps with the application aspect of web 2.0. Defining social media as: collective goods produced through computer-mediated action on web 2.0 services and platforms, gives a better indication on which level of web 2.0 social media operates. This has led to the following distinction between web 2.0 aspects and gives a clear overview of both web 2.0 and social media definitions, that can help identify where the business use of both can be found.

I argue that the business use of web 2.0 can be found in social media. Social media is where the application and platforms that are interesting for the business use of web 2.0 come together and where strategic decisions are made. These platforms offer opportunities for organizations like crowd sourcing, collecting data, marketing and many more. Making use of the collective intelligence aspect of web 2.0 and using social media platforms to collect and share this collective intelligence among the users. In this paper social media is identified as the services and platforms that are interesting for business use and where we the focus will lay on in this paper.

Part 2 follows soon!

The book from Hislop offers an good overview of the KM field, it’s developments and a critical view on KM. Knowledge Management in Organizations: a critical introduction, Hislop D. (2005), Oxford University Press

The list of  Knowledge Management academic papers:

• Keeping the Wheels Turning: The Dynamics of Managing Networks of Practice, Marlous Agterberg et al., Journal of Management Studies 2009
• Supporting Knowledge Creation and Sharing in Social Networks, Rob Cross et al., Organizational Dynamics Vol. 30  2001
• Managing knowledge sharing: Emergent and engineering approaches,
  Hooff & Huysman, Information & Management 46 2009
• The contribution of shared knowledge to IS group performance, Nelson & Cooprider, MIS Quarterly 20 1996
• Transformation Networks in Innovation Alliances – The Development of Volvo C70, Harryson et al., Journal of Management Studies 45:4 June 2008
• Why Should I Share? Examining Social Capital and Knowledge Contribution in Electronic Networks of Practice, Molly McLure Wasko et al., MIS Quarterly Vol. 29 March 2005

Organizations are confronted with the challenge to manage their ‘intellectual capital’ such that they can improve their competitive value. Our teachers have formed a research group on “Knowledge Information and Networks” at KINresearch.nl to help organizations better understand how to manage knowledge.