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This paper aims to examine the relationship between the characteristics of strategic decision-making team’s mental model and its performance. The authors propose that the relationship between mental models and performance is two-way, rather than one-way. Thus, performance feedback should, in turn, influence strategic behavior and future performance by either triggering or hindering the learning process.

The authors conduct the research in the setting of a simulation experiment. A longitudinal data set was collected from 36 teams functioning as strategic decision makers over three periods.

This study provides support for the positive impacts of both the complexity and centrality of a team’s mental model on its performance. The authors also find that positive performance feedback reduces changes in complexity and centrality of team mental models due to cognitive inertia.

The study contributes to the literature by investigating the specific mechanisms that underlie mental model evolution. Different from the existing studies on team mental models that mainly focus on similarity of these shared cognitive structures, this study examines another two characteristics of team mental model, complexity and centrality, that are more relevant to the strategic decision-making process but has not been extensively studied in the team literature. In addition, this study reveals that performance feedback has different effects on team mental models depending on the referents – past performance or social comparison – which advances the understanding of the learning effects of performance feedback.

The implications and influence of different cognitive map structures on decision-making, reasoning, predictions about future events, affect, and behavior remain poorly understood. To-date, we have not had the mechanisms to determine whether any measure of cognitive map structure picks up anything more than would be detected on a purely random basis. We report a Monte Carlo method of simulation used to empirically estimate parameterized probability outcomes as a means to better understand the behavior of cognitive map. Using worked examples, we demonstrate how the results of our simulation permit the use of exact statistics which can be applied by hand to an individual map or groups of maps, providing maximum utility for the collective and cumulative process of theory building and testing.

Antecedents and outcomes of workplace deviance have been studied over the past few decades but there is still a lack of research from an organizational climate, witness and cultural point of view. Theoretical considerations for the present research are based on the social cognitive theory perspective where the authors expect employees's involvement in workplace destructive deviance would depend on their organizational climate perception, witness behavior and cultural orientation.

A total of 987 participants from India (N = 404) and USA (N = 583) completed an online questionnaire, and multi-group structural equation modeling analysis was conducted to test the hypothesized model.

Across cultural groups, higher collectivism is associated with lower engagement in workplace deviance. Furthermore, employees' higher intervening witness behavior is associated with lower destructive deviant behaviors when employees showed higher endorsement of collectivism in India (not USA). However, employees' higher self-serving witness behavior is associated with higher destructive deviant behaviors. Interestingly, employees with higher endorsement of individualism associated with organizational climate are more likely to engage in destructive deviance.

The main originality of this study is to further increase the understanding of the relationship between organizational climate, witness behavior (self-serving and intervening behavior) and workplace deviance (organizational and interpersonal destructive deviance) considering the role of employees' cultural orientation (individualism vs collectivism).

Article explains that institutional knowledge is crucial to the effectiveness of an organization because it enables it to reduce the time and effort needed to explore a novel challenge.

Article tells how to access institutional knowledge and how to foster a culture that respects it.

A supportive culture makes the sharing of institutional knowledge a normal facet of organizational functioning, thereby enabling managers to be highly effective when they have to deal with challenges and opportunities outside their normal routine.

When an organization is threatened by unexpected crises, senior personnel who have gone through previous disasters, can be tapped for some valuable insights into ways of handling the matter quickly and appropriately.

A useful “how-to” guide for integrating institutional knowledge into project management, crisis management, and novel innovation and marketing initiatives.

Sustaining product innovation in an established company – increasingly the key to a company’s economic success, and perhaps its survival – is a challenging task The author describes a and the model often referred to as an “Idea lab” that has emerged as a necessary organizational feature to accomplish this goal.

The author explains how to manage Idea labs as deliberately established locations, where individuals and teams with new product ideas can work together for concentrated bursts of time, sharpening and focusing their product concept, embedding the voice of the customer in product design and charting alternative progression paths for their ideas to be developed into potentially profitable offerings by units of the business that will nurture them.

In today’s organizations, the managerial prime directive is fundamentally being redefined as one of addressing the challenge of sustained, profitable innovation that opens new markets or reinvigorates existing ones. Idea labs should be considered a vital process in fostering sustaining innovation.

A critical success factor is the interplay between idea originators, technology specialists and product managers with a keen awareness of customer needs, competitor initiatives and genuine product differentiation.

A comprehensive guide for top managers and innovators, the article details the four key facets of Idea labs: Positioning in the firm’s innovation value chain. Tasks. Processes. Structure.

This paper aims to analyse the change in performance of parent Indian firms (home effects) who have invested in overseas locations in recent times.

Difference-in-difference (DiD) estimate of home effects using farm level data.

Home effects of Indian outward foreign direct investment (OFDI), in general, are insignificant. However, in the case of OFDI directed only to non-offshore financial centre (OFC), some firms did enjoy beneficial home effects with respect to turnover, current ratio and leverage ratio. In the case of OFDI directed purely to OFC locations, some of the parameters exhibited negative home effects. In the subsample of Indian OFDI directed to combination of OFC and non-OFC locations, the results show positive home effects with respect to export, operating profit margin and forex earnings; however, impact on turnover seems to be negative for all the quartiles.

Estimation of home effects using data over longer horizon may yield robust outcome.

These results make a strong case to draw a distinction among OFDIs to OFC, non-OFC and combination of OFC and non-OFC locations in studying the beneficial home effects of OFDI.

To the authors’ knowledge, this is the first paper which estimates home effects of different groups of Indian firms (based on their investment locations and size class) using difference-in-difference estimate.

This chapter’s focus is comparative causal mapping (CCM) methods in MOC research. For a background, the chapter discusses first the conceptual (cognitive theoretic) basis in typical CCM studies and its implications for understanding the target phenomena and for CCM methods. Next, it presents the CMAP3 software and describes its operating logic and main functions. Third, the chapter describes how to use CMAP3 in three prototypical cases of CCM, each characterized by different research objectives, kinds of data, and methods of data acquisition but also by potential dilemmas. The chapter concludes by speculating about the future directions of causal mapping and suggesting some ideas for developing in particular large-N CCM methods.

The unorganised manufacturing sector contributes one third share of overall manufacturing employment and one fifth share of gross value added of the manufacturing sector. Despite its important role in large-scale employment generation, this sector is neglected by the researchers as well as by the policy makers as compared to the focus given on the organised manufacturing sector. The issues of energy intensity, environment emissions and growth of unorganised manufacturing enterprises (UMEs) remain unexplored. The present chapter attempts to estimate the CO₂ emission and emission intensity (EI) across UMEs on the basis of NSSO Unit Level data of 62nd, 67th and 73rd rounds. It also analyses the growth of UMEs in relation to CO₂ emission and EI. The nature of the sector is very much dispersed. Our study reveals that a portion of unorganised enterprises did not use any energy in their production activities and used manually operated instruments like – handlooms, weaving machines, hand-operated oil and rice mills, etc. The main energy inputs of UMEs are electricity and fuel & lubricants. The CO₂ emission is relatively less in UMEs compared to organised manufacturing enterprises. Across the unorganised manufacturing industries, the higher CO₂ emission are observed in manufacturing of food product industry and other non-metallic mineral industry. The study found that CO₂ EI of UMEs depends on firm-level characteristics like perennial nature, establishment type, urban location and expanding growth status. However, capital intensive UMEs are more polluting.