Research Briefs. “electronic cigarettes do more harm than good”

Research Briefs. 2 at 100 points each.

Students are required to submit 2 research briefs over the course of the quarter. Each will be on a contemporary, newsworthy event. The instructor will assign topics to each student and 1 student will cover each topic.

Research briefs cover two sides of an important issue. They are single spaced, heavily cited (at least 8 sources for each page) research dense work. Remember that these pieces cover two sides of an issue so they can be fairly simple in approach.

Each piece of research will provide 2 pages that oppose. For instance, page one could claim that the Libor scandal proves that the financial system must be revamped. Page two could claim that the Libor scandal proves that the financial system is solid and checks itself for market fluctuations.

Each page will have: 1. An introduction culminating in a clear thesis statement, written like a resolution (ie This house believes the financial system in the US is fundamentally flawed and must have checks and balances) 2. At least 3 paragraphs, heavily cited, with arguments in support of the thesis statement. These paragraphs must be independent arguments for the thesis. 3. A short summary paragraph restating the argument of the paper. Page 2 will have all of these same components but in opposition to the original argument.

My topic is:   “electronic cigarettes do more harm than good”

.Describe an example of a research question where a Chi-squared test has been used.

The Chi-squared test has been used earlier to test a hypothesis about a population variance. It is also a hypothesis testing procedure for when one or more variables in the research are categorical (nominal). During this week, we are covering the following two such Chi-squared tests:  Chi-squared Goodness of Fit Test Chi-squared Test for Independency 1.Describe an example of a research question where a Chi-squared test has been used. Mention the two hypotheses of the problem and display a numerical demonstration of your example. In particular, interpret the test P value in the context of your research example. 2.Describe why the Chi-squared tests of the types mentioned above are always right-tailed hypothesis testing problems.

Transactive Memory Systems

This article was downloaded by: [Carnegie Mellon University] On: 07 March 2014, At: 17:16 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

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Transactive Memory Systems 1985–2010: An Integrative Framework of Key Dimensions, Antecedents, and Consequences Yuqing Ren a & Linda Argote b a Carlson School of Management , University of Minnesota b Tepper School of Business , Carnegie Mellon University Published online: 26 Jul 2011.

To cite this article: Yuqing Ren & Linda Argote (2011) Transactive Memory Systems 1985–2010: An Integrative Framework of Key Dimensions, Antecedents, and Consequences, The Academy of Management Annals, 5:1, 189-229, DOI: 10.1080/19416520.2011.590300

To link to this article: http://dx.doi.org/10.1080/19416520.2011.590300

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Transactive Memory Systems 1985 – 2010: An Integrative Framework of Key Dimensions, Antecedents,

and Consequences

YUQING REN∗

Carlson School of Management, University of Minnesota

LINDA ARGOTE

Tepper School of Business, Carnegie Mellon University

Abstract

Over two decades have passed since Wegner and his co-authors published the groundbreaking paper on transactive memory systems (TMS) in 1985. The concept attracted the interest of management, psychology, and communication scholars who have employed a variety of methods to examine the phenomenon. In this paper, we review 76 papers that examined transactive memory systems and summarize the findings in an integrative framework to show the antecedents and consequences of TMS. Our review also reveals important issues in the litera- ture related to the measurement of TMS, its multidimensional nature, extending TMS from the team level to the organizational level, and the potential role of TMS in explaining the benefits of experience in existing organizations and

∗ Corresponding author. Email:chingren@umn.edu

The Academy of Management Annals Vol. 5, No. 1, June 2011, 189 – 229

ISSN 1941-6520 print/ISSN 1941-6067 online # 2011 Academy of Management DOI: 10.1080/19416520.2011.590300 http://www.informaworld.com

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new entrepreneurial ventures. We conclude by calling for future research to examine the dynamic evolution of TMS, TMS in virtual teams, TMS in entrepre- neurial ventures, and TMS at the organizational level facilitated with information technologies.

Introduction

Over two decades have passed since Wegner and his collaborators first pre- sented the concept of transactive memory to refer to a collective system that individuals in close relationships use to encode, store, and retrieve knowledge (Wegner, Giuliano, & Hertel, 1985; Wegner, 1987). Over the past two decades, researchers from many disciplines including communication, management, social psychology, and information systems have become interested the concept and its effects in group and organizational settings. The concept has been extended beyond its original context of collective remembering in inti- mate couples to work groups and organizations (e.g., Liang, Moreland, & Argote, 1995; Jackson & Klobas, 2008; Lewis, 2003). We have also accumulated a large body of literature regarding the antecedents and consequences of trans- active memory in dyads and work groups. Much of the insight, nonetheless, remains dispersed in separate studies with limited integration.

In this article, we report findings from a comprehensive review of the transac- tive memory literature. We summarize the literature in an integrative framework that shows the antecedents, consequences, and factors that moderate the relation- ship between transactive memory systems (TMS) and various outcomes. Our review suggests four important issues that need to be considered and addressed in future research in terms of (1) using standard scales in measuring transactive memory systems, (2) deciphering the relationships among the dimensions of transactive memory systems, (3) extending transactive memory systems to the organizational level, and (4) investigating the role of TMS in explaining the benefits of experience in existing organizations and new entrepreneurial ventures.

Three observations motivated our decision to conduct a comprehensive review of the literature. First, despite two decades of research, the transactive memory literature remains somewhat fragmented. Researchers choose to study variables of their individual interest and there is little systematic inte- gration such as the input – process – output framework of team effectiveness (Mathieu, Maynard, Rapp, & Gilson, 2008). Although many researchers have examined factors of great interest—such as stress (Ellis, 2006), gender stereo- types (Hollingshead & Fraidin, 2003), and communication (Lewis, 2004), to name just a few—a review is likely to help us integrate accumulated knowledge and identify gaps in the literature for future research.

Second, the growth of the literature increases the likelihood of replicating studies and cross-checking the effects of variables across studies. At the same time, we begin to observe relationships that are inconsistent or even contradict

190 † The Academy of Management Annals

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one another across studies. One example is how the relationship between trust and transactive memory is conceived. Kanawattanachai and Yoo (2007) measured cognition-based trust as a key dimension of transactive memory, similar to the task credibility dimension in Lewis’s 15-item scale (2003). In con- trast, Akgun, Byrne, and Kesin (2005) examined trust as an antecedent to transactive memory systems, whereas Rau (2005) examined trust as a modera- tor of the relationship between transactive memory systems and top manage- ment team performance. A review is likely to help us cross validate insights from different studies and begin to reconcile inconsistencies in the relation- ships between TMS and other constructs.

Third, we hope the review will serve as a vehicle to bridge the gap between theory and practice. While the benefits of TMS have been consistently demon- strated in small groups, there is not much evidence showing its working and benefits in organizations at large, although many organizations have invested heavily in technological solutions to make better use of their intellectual capital (Moreland & Argote, 2003). Part of the answer may reside in the context of the studies that linked TMS to improved performance and the extent to which these findings generalize beyond small face-to-face groups. A comprehensive review allows us to compare findings across methods and contexts and thereby to identify consistencies and inconsistencies in the literature.

In the rest of the article, we first define the concept of transactive memory and present a representation of its key elements. We then describe how we selected the articles to review, together with basic statistics about the literature. We summarize our findings in an integrative framework about the theoretical antecedents and consequences of transactive memory on group outcomes together with factors that moderate the relationship between transactive memory systems and outcomes. We conclude with a discussion of important issues that need to be addressed and our recommendations for future research.

Transactive Memory Systems Defined

The concept of transactive memory systems was first introduced as a mechan- ism to illustrate how individuals can rely upon external aids such as books, arti- facts, or group members to extend individual memory. Wegner, Giuliano, and Hertel (1985) defined the two components of transactive memory as: (1) orga- nized knowledge contained entirely in the individual memory systems of group members, and (2) a set of transactive processes that occur among group members. A TMS consists of a set of individual memory systems in combi- nation with the communication that takes place between individuals (Wegner, 1987). A commonly used definition of transactive memory system is a shared system that people in relationships develop for encoding, storing, and retrieving information about different substantive domains (Hollingshead, 1998a; Ren, Carley, & Argote, 2006).

Transactive Memory Systems 1985 – 2010 † 191

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The Effects Of Communication Networks And Turnover On TMS Argote Et Al

This article was downloaded by: [134.88.77.64] On: 30 April 2018, At: 07:05 Publisher: Institute for Operations Research and the Management Sciences (INFORMS) INFORMS is located in Maryland, USA

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The Effects of Communication Networks and Turnover on Transactive Memory and Group Performance Linda Argote, Brandy L. Aven, Jonathan Kush

To cite this article: Linda Argote, Brandy L. Aven, Jonathan Kush (2018) The Effects of Communication Networks and Turnover on Transactive Memory and Group Performance. Organization Science 29(2):191-206. https://doi.org/10.1287/orsc.2017.1176

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ORGANIZATION SCIENCE Vol. 29, No. 2, March–April 2018, pp. 191–206

http://pubsonline.informs.org/journal/orsc/ ISSN 1047-7039 (print), ISSN 1526-5455 (online)

The Effects of Communication Networks and Turnover on Transactive Memory and Group Performance Linda Argote,a Brandy L. Aven,a Jonathan Kushb a Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213; b Charlton College of Business, University of Massachusetts Dartmouth, North Dartmouth, Massachusetts 02747 Contact: argote@cmu.edu, http://orcid.org/0000-0002-4149-6968 (LA); aven@cmu.edu, http://orcid.org/0000-0001-7086-5876 (BLA); jkush@umassd.edu, http://orcid.org/0000-0003-4872-8650 (JK)

Received: May 28, 2015 Revised: March 8, 2016; December 11, 2016; June 25, 2017; August 17, 2017 Accepted: September 4, 2017 Published Online in Articles in Advance: March 30, 2018

https://doi.org/10.1287/orsc.2017.1176

Copyright: © 2018 INFORMS

Abstract. We theorize that the effect of membership turnover on group processes and performance depends on a group’s communication network. We describe two mecha- nisms through which communication networks affect group performance: (1) the number of direct communication paths and (2) the clarity of the coordination logic. These mech- anisms map onto two network dimensions: density, which affects a group’s behavior through the number of available communication paths, and centralization, which affects a group’s behavior through the clarity of the coordination logic. We empirically analyze the effects of turnover on the performance of fully connected all-channel networks and hub- and-spoke or wheel networks in an experiment of 109 four-person groups performing two collaborative problem-solving tasks. The greater number of direct communication paths enabled fully connected groups with stable membership to develop stronger transactive memory systems (TMSs) and perform better than fully connected groups that experienced turnover. By contrast, the clear coordination logic of perfectly centralized groups that expe- rienced turnover facilitated more frequent dyadic communication, which enabled them to strengthen their TMSs, incorporate the contributions of new members, and improve their performance. Thus, our results indicate that communication networks condition the effect of membership turnover on group processes and performance.

Funding: The authors gratefully acknowledge the support of the National Science Foundation [Grants 1111750 and 1459963] and the Center for Organizational Learning, Innovation and Knowledge at the Tepper School of Business at Carnegie Mellon University.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2017.1176.

Keywords: social networks • turnover • transactive memory • group performance

Introduction Organizational activity comprises the coordination of individuals to solve complex problems. Group mem- bers must identify the expertise of others, access infor- mation held by different members, and coordinate that information to accomplish shared goals. Mem- ber turnover, the exit of an incumbent member and introduction of a new member, in groups can com- plicate the identification and coordination of expertise and information (Arrow and McGrath 1995). Groups with stable membership are able to learn each other’s skills and expertise, allocate tasks to the most qualified members, and coordinate the interdependent activi- ties of their members. When turnover occurs, however, incumbent members know little about the expertise and skills of the new member, and coordination can become challenging (Lewis et al. 2007). Yet new mem- bers can nonetheless be a source of new ideas and per- spectives that improve group performance (Choi and Thompson 2005). We theorize that the effect of turnover on group

performance depends on the group’s communication network. From a network perspective, groups can be

categorized by their structural features—in particular, their centralization (Katz et al. 2004, Leavitt 1951, Rulke and Galaskiewicz 2000) and their density (Freeman 1979, Friedkin 1981, Balkundi and Harrison 2006). Cen- tralization increases for a group as the inequality or variance in the number of connections group members have to others increases. A group’s density increases as the ratio of actual to potential connections increases.

We identify two mechanisms through which a group’s communication network affects performance: (1) the number of direct communication paths avail- able to group members and (2) the clarity of the coordination logic. The first mechanism maps onto network density, which affects a group’s behavior through the number of available communication paths. High levels of density in communication networks allow team members to communicate directly with one another. The second mechanism maps onto net- work centralization, which affects a group’s behavior through the clarity of the coordination logic. Central- ized communication networks direct how information is shared and inform how members coordinate (Blau 1974, Bunderson and Boumgarden 2010).

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Argote, Aven, and Kush: The Effects of Turnover on Group Performance 192 Organization Science, 2018, vol. 29, no. 2, pp. 191–206, © 2018 INFORMS

Figure 1. Fully Connected and Perfectly Centralized Communication Networks

(a) (b)

A

C

DB

A

C

B D

Notes. Panel (a) represents the fully connected communication net- work. Panel (b) represents the perfectly centralized communication network. C is the central member, whereas A, B, and D are peripheral members.

We focus on the two network structures that max- imize one structural dimension while minimizing the other: a perfectly centralized or “hub-and-spoke” net- work that has the highest degree of centralization and minimizes density (see Figure 1), and a fully con- nected, “all-channel” network that maximizes den- sity and minimizes centralization. These two network structures not only allow the investigation of cen- tralization and density in tandem but are also struc- tures common in organizational settings. For exam- ple, programming groups’ communication networks have often been found to be fully connected, where members can communicate directly with any other member in an open-source setting (Tsay et al. 2014). By contrast, particularly in proprietary software, pro- gramming groups generally have a perfectly central- ized communication network where one central mem- ber acts as the “software architect,” and other members can communicate directly only with this central mem- ber (Kruchten 2008, Bosch and Bosch-Sijtsema 2010). In addition, even though project groups in organizations commonly communicate in a fully connected manner, groups engaged in covert projects typically communi- cate in a centralized fashion (Aven 2015).

In the case of stable group membership, high cen- tralization, such as in our perfectly centralized groups, limits direct communication among members through their restricted communication network, which hin- ders members from learning about others’ expertise. Centralized communication networks also force mem- bers to coordinate in a particular manner, irrespective of members’ preferences and abilities. Rather than pro- vide members with the opportunity to customize their coordination logic, centralized group members must channel information to the central member(s), who then orchestrate the group’s activities. Hence, the coor- dination logic in centralized groups is independent of the particular members and their attributes.

When turnover occurs, the communication network of perfectly centralized groups improves the group’s

ability to integrate a new member. The coordina- tion logic of perfectly centralized networks is read- ily discernible by both incumbent and new members, which enhances their ability to contribute to the group (Bunderson and Boumgarden 2010, Morrison 2002). Because members’ roles in perfectly centralized groups are not customized to individual members, it is more likely that the new member can adequately perform the activities of the departing member in centralized than in decentralized groups. Finally, the restricted com- munication pathways in centralized networks require reliance on the few existing pathways to coordinate, which reduces the likelihood that any communica- tion pathway and its respective member are neglected. These factors enable a perfectly centralized group to incorporate the contributions of a new member and improve group outcomes for tasks involving problem solving and creativity (e.g., Wells and Pelz 1966, Choi and Thompson 2005).

When membership is stable, high density in com- munication networks, such as in the fully connected groups, enables members to establish a strong trans- active memory system (TMS), a collective system for encoding, storing, and retrieving information (Wegner 1987, Lewis and Herndon 2011). Because of fully connected group members’ greater ability to communi- cate directly with other members, group members are able to learn about each other’s expertise and, in turn, develop a shared cognitive map of expertise. In addi- tion, fully connected networks allow members to tailor the group’s coordination logic to account for each mem- ber’s preferences and abilities.

Although fully connected communication networks facilitate group performance by encouraging the devel- opment of a strong TMS, fully connected networks can also hinder the integration of new group members when turnover occurs. New members often do not have the same attributes and knowledge as departing mem- bers, which makes the substitution of a new member challenging for these groups because their coordina- tion logic is tailored to the original members’ unique abilities and characteristics. Furthermore, the group’s coordination logic cannot be readily observed by new members, which impairs their ability to contribute to the group.