Monthly Archives: February 2016
Week 06 – IT Governance and Control – paper assignment
| Paper | Student | Background |
| Kirsch et al. (2002) | Yiran | Eisenhardt (1989) “Agency Theory: An Assessment and Review” AMR |
| Xue et al. (2011) | Xinyu | Sambamurthy and Zmud (1999) |
| Banker et al. (2011) | JK | Strategy-structure theory |
| Banker et al. (2011) | Vicky | Preston and Karahanna (2009) |
| Li et al. (2012) | Xue | Sarbanes–Oxley Act |
| Li et al. (2012) | Yae Eun | Feng et al. (1999) |
| Chatterjee and Ravichanran (2013) | Ada | Resource dependence theory |
| Chatterjee and Ravichanran (2013) | Aaron | Sobel mediation test |
Function Point_Xinyu
Please refer to the link below to see what Function Point (FP) is and how it works.
Week 5_Grewal et al.(2006)_Yiran
This paper examined the effects of network embeddedness—or the nature of the relationship among projects and developers—on the success of open source projects. The key of understanding this paper lies in knowing how authors operationalize the key concepts, social capital and network embeddedness. They view social capital as the relations among developers, including project managers, and projects that provide developers access to information and (perhaps) embedded resources. In this paper, they refer the effect of social capital as network embeddedness. The term “network embeddedness” was used to to capture the architecture of network ties, and then three sub-constructs are defined to represent network embeddedness, i.e., structural, junctional, and positional embeddedness. Specifically, they used degree centrality—the number of projects in which the manager participates—to operationalize structural embeddedness, betweenness centrality—the number of paths between other nodes on which the manager lies—to operationalize junctional embeddedness, and eigenvector centrality—the manager participates in important projects—to operationalize positional embeddedness.
The author argued that high-quality information should be more useful in newer projects, and the value of project manager embeddedness should decline as projects age. In this case, Technical success was measured as the number of concurrent versioning system (CVS) commits. With respect to commercial success of the project, since project network embeddedness would facilitate the dissemination of this information. they assumed that the valence of the salient reputation dimension is positive (negative), word of mouth should increase (decrease) the commercial success of the project. Thus, project network embeddedness can have a positive or a negative effect on commercial project success. Commercial success was measured by the number of downloads over the life of a project.
Latent class regression analysis was used to show that multiple regimes exist and that some of the effects of network embeddedness are positive under some regimes and negative under others. The result confirmed that considerable heterogeneity exists in the network embeddedness of open source projects and project managers. Overall, the results for the effects of embeddedness are much stronger for technical success than for commercial success, implying that network embeddedness has a greater role to play in technical success than in commercial success.
Theoretically, this paper recognized that the effect of network embeddedness varies with the dependent variable, i.e., technical or commercial project success. Managerially, the results showed that projects with more developers see greater technical success in the later stages of project development, i.e., as the projects age.
Week5_Bank and Slaughter (2000)_Xinyu
Banker and Slaughter (2000) initiates an effort to study the link between software design decisions and software enhancement outcomes. They examine under what conditions software structure is more beneficial than other conditions in terms of reduced enhancement costs and errors.
In specific, they introduce software structure as a moderator of the relationship between software enhancement outcomes and two properties of software, namely software volatility (the frequency of enhancement per unit of functionality) and total data complexity (the number of data elements per unit of functionality). While software volatility and total data complexity are proposed to be positively associated with software enhancement outcomes for intuitive reasons, higher levels of software structure are proposed to mitigate those impacts on the enhancement outcomes. This is because structured software allows maintainer to focus particular issues on only the particular parts after getting familiar with the software through the practice of frequent enhancement, and structured software can be easily simplified by structural decomposition, thus the enhancement costs and errors will be reduced. However, since excessively high levels of structure are also redundant and problematic, the paper also discusses optimal levels of structure for different types of software applications.
The empirical results confirm that higher levels of structure are more advantageous for software with higher volatility and complexity, in terms of reducing enhancement costs and errors. Empirical evidence also shows that the optimal level of structure increases with software volatility and complexity. Finally, the paper identifies application type as an indicator for predicting future volatility and complexity, so that an optimal level of structure can be achieved at an early stage.
Week5_Krishnan et al. (2000)_Vicky Xu
An Empirical Analysis of Productivity and Quality in Software Products
Most of prior empirical research on software maintenance has not been able to provide answers to problems related to cost overrun since productivity and quality modeling efforts have often considered either the productivity or the quality. And empirical evidence on the effect of process factors is mostly restricted to case studies and experience reports of a few projects.
Krishnan et al. (2000) fill this void by examining the relationship between life-cycle productivity and conformance quality in software products. Krishnan et al. (2000) address the research questions as following:
- What is the trade-off between quality and life-cycle productivity?
- What are the effects of the development process on life-cycle productivity and quality?
- Does up-front resource deployment pay off?
- What are the effects of development resources on productivity and quality?
The conceptual elements of the research model in this paper (is shown in Figure 1., p. 748) as the following diagram:
Krishnan et al. (2000) collected data on commercial software projects of a leading vendor. Then, Krishnan et al. (2000) consider the software process areas specified in the Capability Maturity Model (CMM) that are relevant to software productivity and quality, and consider alternate specifications (linear versus nonlinear) for the relationship between various explanatory variables and quality or life-cycle productivity. And the estimation procedures include OLS, SUR, and 2SLS.
Krishnan et al. (2000) find: (1) Evidence for both direct and indirect (through quality improvement) effects of personnel capability on software development and maintenance productivity. (2) Investments in the early stages of software development improve quality. (3) Several quality drivers in software products.
Three main contributions of this paper are: (1) Developing models for software life-cycle productivity that include both development and maintenance costs. (2) The models can capture the effect of the software development process measured at the project level based on the practices specified in CMM key process areas on life-cycle productivity and quality. (3) Studying the effect of front-end investment in product development on conformance quality. (4) Validating the proposed models by using primary data on system software projects of a large commercial software developer.
Week 5_Ramasubbu and Kemerer (2015)_Jung Kwan Kim
Ramasubbu and Kemerer (2015) examine the technical debt and the interdependency between client and vendor maintenance activities. Their analysis reveals that there do exist the dynamics of technical debts reduction and its impact on the reliability of commercial-off-the-shelf (COTS) systems.
One of the fundamental findings is that technical debt is “associated with an increase in the probability of a system failure” because it increasingly deteriorates knowledge asymmetry between vendors and clients. Modular maintenance by clients ameliorates the reliability of a system through reducing the errors due to clients more than architectural maintenance does mainly because details in architectural knowledge of a system are not well disseminated to clients’ software teams. Interestingly, modular maintenance is more likely to increase the probability of system failure due to vendor errors than architectural maintenance is. This contrasting findings is supported by the fact that modular maintenance by clients may not consider the overall architectural structure of a system, leading to conflicts with a new version of the system or a vendor-driven platform updates.
The empirical contributions of Ramasubbu and Kemerer (2015) deserve highlighting. The newly devised competing risks analysis shows the different impact of the trade-off relationship between modular and architectural maintenance on vendor vs. client errors. Mediation analysis clearly shows the mediating impact of technical debt between each type of maintenance and system failure due to client errors. The analysis is useful to present the existence of “benefit zone” out of the trade-off effect, suggesting that discretionary decision on maintenance should be employed.
Week5_Subramanyam et al (2012)_Xue Guo
In Search of Efficient Flexibility: Effects of Software Component Granularity on Development Effort, Defects, and Customization Effort
This paper mainly examines the relationship between software component design dimensions and software development outcomes in the context of model-driven, component-based software development (MDCD). It explores how different software design dimensions affect the trade-off between efficiency and flexibility.
The authors proposed that component granularity design (fine-grained & coarse-grained) decision plays an important role in the relationship between realized development efficiency and flexibility, i.e. the coarse-grained component would be associated with greater flexibility but less efficiency. The paper also proposes that mediating effect of in-process defects between component granularity and the development and customization efforts.
This paper empirically tests the effects of component granularity on development efficiency and flexibility from a sample of 92 data. The empirical models contain three dependent variables: in-process defects, development effort and customization effort. And the main independent variables include three measures of the component granularity: data elements, data layer interfaces and internal interfaces. The paper uses three-stage least squares regressions (3SLS) to address the simultaneity among certain measures and seemingly unrelated regression (SUR) to examine consistency of results. And it tests the hypothesis by conducting join tests for three measures of the component granularity. The empirical results support all of the author previous hypothesis.
The contribution of this paper is that it provides three measures of component granularity which match with the generic structural complexity dimensions and empirically establish the importance of component granularity design decision on the trade-offs between efficiently and flexibility.
Week5_Subramanyam et al. (2012)_Aaron
In Search of Efficient Flexibility: Effects of Software Component Granularity on Development Effort, Defects and Customization Effort
The trade-off between efficiency and flexibility in enterprise software production poses a big challenge for firms. New software development paradigms emphasize modular design of complex systems to overcome such challenge. However, there remains little understanding on the use of such software methodologies and associated extent to such trade-offs that can be influenced.
Subramanyam et al. (2012) addressed this gap by investigating the performance outcomes of a model-driven, component-based software development methodology. Specifically, they discuss how a design characteristics of software components, component granularity (with sub-dimensions of code volume, functionality and independence), affects development efficiency (development effort and in-process defects) and flexibility (customization effort).
To test such effects, they utilized a cross-sectional dataset that covers the software development information about 92 business software components of a firm’s enterprise resource planning product. Through 3SLS and SUR analysis, they found that coarse grained components are associated with higher flexibility but are associated with lower development efficiency. Moreover, they found that defects partially mediate the relationship between component granularity and flexibility.
The key implication from this study for software managers and designers who seeks to adopt modular design approaches is that active and judicious management of component granularity resulting from the decomposition of complex enterprise systems is necessary to simultaneously achieve flexibility and efficiency in software development.
Week5_Grewal et al.(2006)_Yaeeun Kim
This article examined the effects of network embeddedness on the success of open source projects. The authors assume heterogeneity and investigated how these structure differ across project and managers. They showed that there is significant effect of network embeddedness on technical and commercial success. By using latent class regression analysis, they showed that different aspects of network embeddedness have powerful but subtle effects on project success. In this case, the valence of word-of-mouth (WOM) decides the success (the number of page view or downloads).
According to the social contagion, positive WOM within the network of users would result in more users visiting the project websites (externality), and leads to commercial success. However, they assume that negative WOM would make a decrease in outcome (or the number of downloads).
The result shows that project network embeddedness positively influences project technical success, while the effect of project manager network embeddedness is more complex and different for older projects when compared with younger project. They used centrality for method: degree centrality is the number of projects in which the manager participates (structural embeddedness), betweenness centrality is the number of paths between other nodes on which the manager lies (junctional embeddedness), and eigenvector centrality is the manager participates in important projects (positional embeddedness).
In summary, the article shows that the effect of project network embeddedness positively influenced project technical success. However, the effect of project manager network embeddedness varies in the year of project. As a result, the network embeddedness was more influential to technical success, which were attractive to developers visually, but the influence was less powerful in commercial success, which were less visible to users.
Week 5 Ada—Ramasubbu and Kemerer (2015)
Technical Debt and the Reliability of Enterprise Software Systems:
A Competing Risks Analysis
Key Concept:
Technical Debt: Taking design shortcuts and other maintenance activities software organizations incur what has been referred to as technical debt, that is, accumulated maintenance obligations that must be addressed in the future
Motivation:
Technical debt reduction in an enterprise software systems environment is difficult, and maintenance of such systems is especially challenging because of the interdependencies and potential for conflict between the underlying, vendor-supplied platform and the customization done by individual clients. These interdependencies make it difficult to measure and assess the impact of technical debt on system reliability and therefore to plan the software maintenance activities necessary to reduce the debt.
Research Question:
- Model and empirically analyze the impact of technical debt on system reliability.
- Examine the relative effects of modular and architectural maintenance activities undertaken by clients in order to analyze the dynamics of technical debt reduction.
Main Findings:
- Technical debt decreases the reliability of enterprise systems.
- Modular maintenance targeted to reduce technical debt was about 53% more effective than architectural maintenance in reducing the probability of a system failure due to client errors.
- Modular maintenance had the side-effect of increasing the chance of a system failure due to vendor errors by about 83% more than did architectural maintenance activities.
Contributions:
- This study empirically measure the technical debt accumulated in real world enterprise software and to assess its dynamic impact on system reliability.
- They address this challenge by utilizing a competing risks analysis approach that account for event-specific hazards that impact the failure of enterprise software systems.
- They utilize the empirical results to illustrate how firms could evaluate their business risks exposure due to technical debt accumulation in their enterprise systems and assess the likely effects, both positive and negative, of a range of software maintenance practices.
Competing risks:
Competing-risks survival regression provides a useful alternative to Cox regression in the presence of one or more competing risks. For example, say that you are studying the time from initial treatment for cancer to recurrence of cancer in relation to the type of treatment administered and demographic factors. Death is a competing event: the person under treatment may die, impeding the occurrence of the event of interest, recurrence of cancer. Unlike censoring, which merely obstructs you from viewing the event, a competing event prevents the event of interest from occurring altogether, and your analysis should adjust accordingly. As a technical consequence, an individual observed to fail from a competing risk is assumed to still be at risk between its real-life failure time and its potential future censoring time.
This fact has two important implications. First, the naïve Kaplan–Meier that takes the competing events as censored observations, is biased. Secondly, the way in which covariates are associated with the cause-specific hazards may not coincide with the way these covariates are associated with the cumulative incidence.
A complete understanding of the event dynamics requires that both cause-specific and sub-distribution hazards to be analyzed. The difference between cause-specific and sub-distribution hazards is the risk set. For the cause-specific hazard the risk set decreases each time there is a death from another cause censoring. With the sub-distribution hazard subjects that die from another cause remain in the risk set and are given a censoring time that is larger than all event times.
Week4_How to work with your advisor?
Discussion topic: How to work with your advisor?
Pang: There are two important principles:
- Your advisor is not your boss.
- Your advisor is not doing your research for you.
Let’s talk about what the first principle means. How is an advisor different from a boss?
Student1: A boss and an advisor are different in that an advisor gives guideline for what you are doing, while a boss gives you what you should undertake and follow.
Pang: Right. In your research, you are the boss, not your advisor is. You don’t need to do everything that your advisor tells you to do. If you only follow your advisor’s instructions, you are no more than his/her research assistant. You should be the boss for your own project, dissertation, or job market paper.
I understand that to Asians, what a teacher says is always God-given truth. You must change such a mentality. Sometimes, you have to have a courage to disagree with your advisor and should be able to convince him/her why your way is better. If you can’t convince your advisor, how would you convince your editor or reviewers?
Pang: What do you think with the second principle? – Your adviser is not going to do research for you.
Student2: You should be an independent researcher.
Student3: From my own experience, I had to recheck and have a second look at a paper before submitting it, because I am responsible for it.
Student4: We should be the one who pushes your project forward.
Pang: Yes, you should be the one who manages your research. The bottom line is, your advisor is not going to solve your problems. His/her role is helping you do quality research and complete it, not offering solutions to you every time you hit a wall. “My advisor does not let me graduate..” does not really make sense from this perspective.
Student5: I think the relationship between a student and an advisor varies in disciplines.
Pang: True, but in a business school, as we’ve been discussing, you are expected to become an independent researcher. Remember this – Don’t blame your advisor when your research goes south. Your advisor is not the person who solves every problem of yours. It is your job.
You are the one who knows the most about your project. An advisor often does not know everything about your work. At a conference presentation, I’ve seen a professor talking to the audience that “I don’t know why my student chose this method..” He may not be supposed to say it, but he was likely telling the truth. Since you’re the boss in your research, you make the decisions, and therefore, you’re responsible for it.
Pang: I also want to talk a little about who should be your advisor. It might be a good idea to have two advisors – a senior professor and a junior/assistant professor. There is a study in a science discipline that the most cited papers are ones with a three co-author combination – a doctoral student (first), a junior faculty (second), and a senior professor (third). The doctoral student is the one who came with up the idea, did the bulk of the analyses, and wrote most of the paper. What are the roles of the other two co-authors, then?
Student1: The senior advisor provides a big picture, and the junior advisor provides detailed skills.
Pang: That’s right. The junior advisor can provide hands-on and detailed skills and tacit/intimate knowledge on how to make a progress in research, how to get it done. The senior professor, on the other hand, can provide a big picture: What is interesting to reviewers, what is not, how to frame/sell the paper, and what contribution the paper makes, and etc. This is a complementary role between the senior and the junior faculty members.
Week 05 – System Development – paper assignment
| Paper | Student | Background |
| Krishnan et al. (2000) | Vicky | Capability Maturity Model (Krishnan and Keller 1999) |
| Bank and Slaughter (2000) | Xinyu | Function points |
| Grewal et al. (2006) | Yiran | Social capital |
| Grewal et al. (2006) | Yae Eun | Measurement of centrality (degree, between, eigenvalue) |
| Subramanyam et al. (2012) | Aaron | 3SLS, Seemingly unrelated regression |
| Subramanyam et al. (2012) | Xue | Measurement of component granularity (Messerschmitt 2007) |
| Ramasubbu and Kemerer (2015) | Ada | Competing risks analysis (Fine and Gray 1999) |
| Ramasubbu and Kemerer (2015) | JK | Henderson and Clark (1990) |
Literature Review – due by Friday, March 4, 11:59 PM
The literature review assignment is due by Friday, March 4 at 11:59 PM EST. Submit your file by email to minspang@temple.edu.
- Topics should be from the ones listed in the course schedule or closely related to them.
- The literature review should be no more than five-page long in double-space, 11-point text, one inch-margin in all four sides.
Ceccagnoli 2012—Yiran Week 4
This paper investigated whether participation in an ecosystem partnership will improve the business performance in the context of the enterprise software industry (ISV). The key research questions of this study are (1) Is participation in a platform ecosystem, on average, associated with an increase in performance? (2) How is this improvement in performance affected by an ISV’s ownership of IPRs and specialized downstream capabilities? Two critical performance measures for ISVs were used as DV in this paper: sales and the likelihood of obtaining an initial public offering (IPO). They used a longitudinal data set of 1,210 small ISVs over the period of 1996 – 2004, with information on both ISVs’ decisions to join SAP’s platform ecosystem and information on their business performance. To operatize the participation in platform ecosystem (IV), they also collect partnership formation events through press releases. The stock of software trademarks registered in the United States is used as the measurement of another IV. The research framework is shown in Figure 1
.
Except for H4b, all the hypotheses are supported, showing that ISVs can achieve significant benefits through participation in a platform ecosystem. Joining a major platform owner’s platform ecosystem is associated with an increase in sales and a greater likelihood of issuing an initial public offering (IPO). Furthermore, these impacts are greater when ISVs have greater intellectual property rights or stronger downstream capabilities. The theoretical contribution lie in implying strong IPRs directly mitigate the negative impact of technology commercialization by ISVs. by affecting the likelihood of platform owner entry. In other words, IPRs appear to favor both value appropriation and value cocreation in the enterprise software industry
Week4_Tafti et al. 2013_Aaron
Extant IS studies have focused on the effects of IT in reducing transaction and coordination costs in inter-organization relationships, there has been little understanding regarding the role of flexible IT architecture as an enabler of interfirm collaboration.
Ali Tafti et al. (2013) fill this academic vacuum by investigating the effects of information technology architecture flexibility on strategic alliance formation and firm value. Specifically, they first examine the effect of three dimensions of IT architecture flexibility (open communication standard, cross-functional transparency, and modularity) on formation of three types of alliances (arm’s-length, collaborative, and joint-venture alliances, respectively.) Second, they study how capability in IT flexibility moderate the value derived from alliances.
To establish the relationship between IT architecture flexibility, strategic alliances and firm value, they utilize a data set from 169 firms that are publicly listed in the US and that span multiple industries. Through panel random-effects models along with several techniques to address potential effects of endogeneity and simultaneity, they found that adoption of open communication standards is associated with the formation of arm’s-length alliances, and modularity of IT architecture is associated with the formation of joint ventures. They also found that the value of alliances is enhanced by overall IT architecture flexibility, implying that all three dimensions of flexibility are important in the value derived from arm’s-length, collaborative and joint-venture alliances.
This study suggests a need for greater consideration of the role of flexibility in IT-driven business process to understand the underpinnings of IT business value in inter-organizational context.
Week4_Tanriverdi & Uysal (2011)_Yaeeun Kim
This paper considered the cross-business information technology integration (CBITI) capability of an acquirer as a potential value-creation mechanism in M&A. This study contributes to the M&A streams within the finance and strategy literature by explaining how and why the CIBTI capability of an acquirer following an acquisition.
In examining the short-run abnormal stock returns, capital markets are indifferent to whether the value will be created out of potential synergies in similar resources of related targets or complementary resources of unrelated targets, but it showed significant result when CBITI capabilities. Event study method was used to measure forward-looking expectations of the capital markets about the value-creation or destruction effects of CBITI in a new M&A. This method assumes that capital markets are efficient (efficient market hypothesis), incorporating into the stock price of the acquirer all relevant information about the acquirer. By setting an event day as 0, the event window is set as five-day [-2, 2], and examining the difference of actual returns and expected returns that when M&A was not announced.
In examining long-run abnormal operating performance (AOP), industry relatedness of a target was significant in moderation effect. Interestingly, the complexity of structure does not deter for superior CBITI capabilities integrate the complementary resources of unrelated targets acquired from different industries. To compute the long-run AOP of an acquirer after a new acquisition, an event study method was used again. This method is designed to capture changes in accounting-based measures of a firm’s operating performance relative to a benchmark, such as M&A. Industry benchmark minimizes problems such as differences in the prevent characteristics of firms leading to operating performance differences before the impact of the M&A event under consideration.
Week4_Tanriverdi and Uysal (2011)_Xinyu
Tanriverdi and Uysal (2011) theoretically develop and empirically validate the idea that the cross-business information technology integration (CBITI) capability of an acquirer is an important value-creation mechanism in mergers and acquisitions.
The paper proposes that CBITI capability create acquirer value through 1) IT cost savings, 2) minimization of potential disruption to business operation, 3) realization of business synergy, and 4) reduction of regulatory costs. Based on prior literature, the CBITI capability is measured by five dimensions of the IT integration of acquirer and target firms, and the data is collected from a survey published in Tanriverdi (2006). The value created in mergers and acquisitions is divided into short-run market-based value and long-run accounting-based value, which are observed through event study methods on capital market and firms’ operating performance, respectively. The value creation is proposed to be moderated by the industry relatedness between acquirer and target firms, which is also measured by the survey.
The findings indicate that, in the short run, acquirers with high levels of CBITI capability receive positive and significant abnormal returns on the capital markets. In the long run, acquirers with high levels of CBITI capability obtain significantly higher abnormal operating performance. However, the moderating effect of industry relatedness is only found in the long run scenario.
It is the first paper that link the construct of CBITI with mergers and acquisition performance.
Week 4_Chellappa et al. (2010)_Jung Kwan Kim
The research of Chellappa, Sambamurthy, and Saraf (2010) is motivated by conflicting arguments in strategy literature to respond the question: is it beneficial to participate in a crowded market or not? By examining the enterprise systems software (ESS) industry, the authors argue that the detrimental effect of being in a crowded market can be counteracted by the virtuous effect of demand externality.
More specifically, the authors suggest that “the performance of an ESS firm is positively related to its degree of multimarket contact with the other ESS firms” (Hypothesis 1). This is mainly because ESS firms in a market may enjoy the mutual forbearance to secure higher market performance if they are more familiar with and more fearful to each other based on the possibility of retaliation. The Hypothesis 2 is also supported, though weakly, saying that “the performance of an ESS firm is positively related to its degree of participation in crowded markets, or the extent of market domain overlap.” The customers perceive the presence of many ESS firms in a market as a positive signal about the importance and the legitimacy of the component in the market. Also, the crowded market attracts more knowledge brokers (such as consultants), reinforcing the legitimacy and the viability. Thus, the participation in a crowded market may bring a positive performance, though the outcome can be somewhat mitigated by the intensity of competition. Finally, the Hypothesis 3 contends that “the positive effects of ESS firms’ participation in crowded markets are increased by the level of multimarket contact with other ESS firms.” This hypothesis is also supported in that an ESS firm in a crowded market with high multimarket contact understands rivals better and in that such ESS firm has more ways to retaliate any rivalrous activities of other similar firms.
In conclusion, ESS firms may benefit from competing in many crowded markets, a counterintuitive implication to traditional strategy scholars.
Week4_Chellappa et al (2010)_Xue Guo
Competing in Crowded Markets: Multimarket contact and the Nature of Competition in the Enterprise Systems software industry
This paper examines the performance consequences of competition among enterprise systems software (ESS) providers. The authors provide reasons for the appearance of ESS firms in the crowded markets and shed light on ESS firms’ strategies in competitive markets.
The paper mainly discussed the effects of multimarket contact and participation in crowded market on ESS firms’ performance. Based on the previous literature about the mutual forbearance and crowded market structure, the authors proposes that multimarket contact can foster mutual forbearance, which is positively related to firm performance, and the participation in crowded market also positively associated with firm performance by demand externalities.
The authors empirically test the hypothesis by a merging dataset across three time periods. It builds a random effect model, which contains the dependent variable—firms’ performance and the main independent variables—multimarket contact, participation and the interaction term of these two. Also, the authors incorporate a temporal lag between Dependent Variable and the other variables to avoid causal ambiguity. The results showed that the coefficient of multimarket contact and the interaction term is positive and significant. The coefficient of participation is weakly significant. These results suggest that firms do not benefit by offering a large number of software components. However, firms stand to benefit if they strategically choose specific market. In addition, firms gain performance benefits by competing in the crowded market but it may be diluted by increased market overlap and competitive rivalry.
This paper contributes to the literature by further examining performance consequences in crowded market of ESS firms and studying the joint effects of multimarket contact and market overlap on ESS firm performance. At the same time, it provides meaningful implications for firm strategy and management.
Week4_Chi et al. (2010)_Vicky Xu
Information Technology, Network Structure, and Competitive Action
Over the last 20 years, firms have increasingly used IT to create and manage their interfirm networks. And prior studies tried to explore the relationships among the structural properties of interorganizational networks IT use, and competitive behavior. However, more researches on the complex interplay between different types of network structure and IT and their effects on competitive behavior of firms are needed. Chi et al. (2010) focus on the sparse-versus-dense network structure of interorganizational networks and aim to examine how two different types (Sparse and dense) of network structure interact with IT to influence firm competitive action which has examined three recognizable patterns as: action volume, action complexity, and action heterogeneity.
Chi et al. (2010) present the theoretical model as following (Figure 1, p546):
Chi et al. (2010) collected a sample of firms from the global automobile industry (SIC 3711) that sell autos in the U.S. market to test the hypotheses in the study. The firm-level panel data from 1988 to 2003 includes: competitive action data, alliance network data, and IT-enabled capability data. The random-effects model was performed to analyze the data.
Chi et al. (2010) find that network structure rich in structural holes has a positive direct effect on firms’ ability to introduce a greater number and a wider range of competitive actions. And firms benefit from dense network structure only when they develop a strong IT-enabled capability. In addition, firms can use IT to complement both types of network structure to increase all three behavioral drivers for competitive actions.
The contributions are: 1). Presenting an attempt to systematically explore the significant interplay between interfirm network and IT. 2). Contributing to research on IT valuation by demonstrating the moderating role of IT-enabled capability on the effects of network structure on firm action. 3). Advancing competitive dynamics research by showing how sparse-verse-dense network structure differentially affects competitive behavior of firms. 4). Extending the awareness-motivation-capability (AMC) framework by focusing on attributes and patterns of competitive action repertoire. 5). Important practical implications which suggest that managers need to consider the network structure in which their firms are embedded when designing their technology infrastructure.