Search results

The purpose of this paper is to review behavioral explanations of the empirical observation that investment managers in mutual fund companies increase their risk taking when offered incentives based on how their performance is ranked compared to peers.

A conceptual model is proposed of how research on social comparison, competition and financial risk taking may explain increased investor risk taking induced by rank-based incentives. Research findings in each of the strands of research are reviewed.

A proposed main explanation is that an above-average bias in comparing oneself with competitors results in overconfidence that increases risk taking. A complementary proposed explanation is that an anticipated loss when lagging behind increases risk taking, and another proposed complementary explanation the belief that risk taking is a winning strategy.

The results provide a broad framework for directions of research on social comparison processes in the mutual fund industry addressing the difficulties in implementing performance evaluations.

The purpose of this paper is to investigate how social comparison and motivation to compete account for elevated risk-taking in fund management corroborated by asset market experiments when performance depends on rank-based incentives.

In two laboratory experiments, university students (n1 = 240/n2 = 120) make choices between risky and certain outcomes of hypothetical sums of money. Both experiments investigate in which direction risky choices in an individual condition (individual risk preference) are shifted when participants compare their performance to another participant's performance (social comparison), being instructed or not to outperform the other (incentive to compete).

In the absence of incentives to compete, participants tend to minimize the differences between expected outcomes to themselves and to the other, but when provided with incentives to compete, they tend to maximize these differences. An independent additional increase in risk-taking is observed when participants are provided with incentives to compete.

Original findings include that social comparison does not evoke motivation to compete unless incentives are offered and that increases in risk-taking depend both on what the other chooses and the incentives.

Over recent decades, talent agglomeration has emerged as a critical topic for scholars, businesses and government officers. Innovative ability is a core competition for high-tech talents. In China, low innovation is the bottleneck, as the high-tech industry usually cannot provide sufficient support for the continuous needs of innovative talents. To enhance the continuous support of talents, it is important to obtain the mechanisms of talent evaluation and flow in high-tech industry. Exploring the incentive factors influencing the scientific and technological personnel, adjust the layout of talents and promote the rational agglomeration. It’s significant to realize the regional economic development.

This study proposes an assessment model using the multi-criteria decision-making method of analytical hierarchy process (AHP) to determine the weights of incentive factors and a nonlinear programing model, from micro, meso and macro perspectives of individual, organizational and social incentives by adopting Maslow’s hierarchy of needs theory, Kurt Lewin’s field theory and Lee’s push-pull theory. After the literature review and interviews with 14 experts, this study produced a research framework and a pairwise comparison questionnaire. In addition, the relative quantitative weights of 3 main categories and 15 indicators are identified and ranked based on the AHP method.

The results demonstrate that the most important dimension is the individual, and the top three highest weighted factors are job satisfaction, sense of working accomplishment and interpersonal relationships. The discussion in this study showed that the proposed model is rational and acceptable to motivate high-tech innovation talent (HTIT) agglomeration for high-tech enterprises, universities, government and start-ups.

The pairwise comparison using the AHP method is limited to expert opinions, which are considered comparatively subjective. The number of incentive factors should be increased, as some indicators may have been omitted from the AHP model.

According to the results, some suggestions can be recommended to corporate executives, HR managers and government officers to attract and retain high-tech talents and further to improve industrial clusters and economic development.

This paper derives a relative ranking of importance based on the opinions of experienced HR specialists, high-tech talent, scholars and government official, and assesses the consistency of results. The ordering represents the importance of indicators and sub-indicators of two levels from respondents’ perspectives in an industry cluster background. The study, focusing on the high-tech industry in China (which is a developing country), offers a unique view, as earlier studies mainly collect data from developed countries.

The purpose of this paper is to analyze how long-run unemployment of former apprentices depends on the size of their training firm and their ability.

The authors use a large administrative data set that follows graduated apprentices during their working life. They show that training in large and medium-sized firms is associated with considerably less unemployment. This, however, may simply be the result of sorting processes, i.e. larger training firms with higher wage levels attract and choose the most able young workers. Therefore, the authors use a proxy for ability to estimate and control for the impact of ability on long-run unemployment. They assume that rank-order tournaments for the most attractive training positions take place and take into account an institutional peculiarity of the German training system, the empirically observable regional immobility of apprentices. Accordingly, they use a region-specific ranking based on training plants’ size or median wages, respectively, to proxy for apprentices’ ability.

The negative association between training plant size and long-run unemployment is muted but still statistically well determined even after controlling for the rank of an individual’s training firm in the local plant size distribution or the local wage distribution, respectively. Thus, the rank itself is a predictor for long-run unemployment of apprentices. The fact that the position in the local size distribution matters conditional on plant size shows that there is a local competition for training places.

Lacking mobility may increases aggregate unemployment, as mobility reduces the risk of unemployment.

The results imply that supporting regional mobility of young workers, e.g., by informing them better about existing mobility subsidies and dormitories for apprentices and by creating additional mobility incentives is warranted.

This is the first study to investigate long-run unemployment of former apprentices. Furthermore, the authors develop new variables to proxy for ability.

Scarcity of resources and ever-changing customer demand has driven the manufacturing organization to opt for an integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS). The purpose of this study is to identify and rank the various drivers for the adoption of ISGLSAMS for the more sustainable development of the industries.

Using a survey questionnaire, data were collected for the 14 ISGLSAMS drivers, identified through the literature review, from 108 Indian manufacturing industries. The sign test is used to check the relevance and significance of drivers. ISGLSAMS drivers are ranked based on the median and standard deviation. A multiple regression model was employed to investigate the effects of other drivers on the highest-ranked driver to strengthen the understanding of the drivers.

Competition, customer demand, technological changes, supply chain pressure, cost benefits, incentives, top management commitment and future legislation are found the strongest drivers for ISGLSAMS. For administering the competition for ISGLSAMS policymakers must focus on the availability of organization resources, customer demand, future legislation, incentives, supply chain pressure and technological developments.

The study contributes to a better understanding of ISGLSAMS drivers. Through this study government, stakeholders and policymakers may plan the policy, roadmap and strategies to drive the manufacturing organizations for the adoption of ISGLSAMS for more sustainable development of industries in India.

This work contributes to the identification and prioritization of the drivers for the more sustainable manufacturing system, i.e. ISGLSAMS (7 Rs based, i.e. 6 Rs of sustainability with 7th R, reconfiguration). The research also contributes to the (1) ISGLSAMS literature (2) the awareness and demand of (a) ISGLSAMS (b) reconfigurable, sustainable and modular products (c) redesign, recovery and refurbishing of the product to increase the product life cycle.

Tournament theory provides important insights into organizational reward systems. It examines the incentive properties of reward systems based on rank‐order rather than absolute individual performance. Tournament theory may explain the pattern of managerial pay. It may also explain risk‐taking behavior by mutual fund managers. We use data from the PGA tour to examine the pattern of risk‐taking by professional golfers in an explicit tournament. The PGA tour provides a natural laboratory where such behavior can be studied. Our evidence shows that behavior by players in golf tournaments is consistent with the predictions of tournament theory.

The purpose of this paper is to identify critical success factors (CSFs) that are regarded as the most important in Six Sigma programs in Brazil and to compare these rankings with those in international literature.

A sample of industrial companies was selected to complete a survey. In total, 104 questionnaires were obtained. The results were compared with a literature review consisting of 26 papers from 13 countries. In total, 70 CSFs were found in the papers, but 19 CSFs were analyzed and reduced to ten. A multivariate factor analysis further reduced this number to two underlying constructs.

The authors identified a CSFs common denominator/ranking based on the sample of international articles. The authors found that there are four CSFs that are more prevalent in Brazil and in the international papers studied and that there are no differences between the importance of CSFs in terms of hierarchical levels. Three gaps, five levers and two CSFs constructs were identified.

This study may initiate cooperation between the studied companies and academia, thus possibly increasing these organization’ knowledge regarding Six Sigma.

The originality of this study is that the survey was conducted with companies in Brazil, a country where little information exists on Six Sigma programs. The authors also contributed a literature review on CSFs, a comparison based on most of the consulted papers and the use of a robust methodological strategy that was made possible by the sample size.

This study aims to uncover the determinants of Islamic financial inclusion in Indonesia.

This study uses the analytic network process (ANP) to gather expert opinions and responses from academics, regulators and practitioners.

The ANP analysis discovered that the level of Islamic financial inclusion in Indonesia is influenced by two main drivers: the supply and the demand. The demand factors for Islamic financial inclusion, ranked based on their level of significance, are as follows: financial literacy (0.27), religious commitment (0.22), socioeconomic factor (0.19) and social influence (0.17), respectively. From the supply side, primary catalysts for Islamic financial inclusion based on their level of importance are human capital (0.32), product and services (0.24), infrastructure (0.18) and policies and regulation (0.17), respectively.

The present study does not include the Islamic insurance sector in its determinant framework of Islamic financial inclusion in Indonesia.

This study serves as a reference for regulators in formulating appropriate policy strategies to strengthen the Islamic financial inclusion in Indonesia.

This study is a pioneer attempt to identify distinctive factors that influence the level of Islamic financial inclusion in Indonesia by analyzing expert opinions from diverse groups of Islamic finance stakeholders.

The present study aims to seek the strategic analysis of the entrepreneurship of agricultural colleges (AC).

In terms of approach, this research was a combination of exploratory and hybrid methods. The present study was conducted in four stages. In the first stage, an open-ended questionnaire was designed to identify the strengths, weaknesses, opportunities and threats of entrepreneurship in AC (qualitative method). In the second stage, the Delphi-Fuzzy questionnaire was designed based on the results obtained from the first stage. In the third stage, the criteria of strengths, weaknesses, opportunities and threats of entrepreneurship of AC were analyzed based on the pairwise comparison (quantitative method) by the sample using a fuzzy hierarchical analysis process (FHAP). In the fourth stage, presented strategies were ranked based on pairwise comparison using FHAP.

From the analysis of weaknesses, strengths, opportunities and threats facing AC for entrepreneurship, 12 strategies were presented in 4 groups of aggressive, conservative, competitive and defensive.

The literature review showed that no research has been done so far to identify strengths, weaknesses, opportunities and threats facing university entrepreneurship, especially AC. So the present study analyzes the weaknesses, strengths, opportunities and threats and proposes practical strategies for moving toward the formation of entrepreneurship AC. According to the gaps in providing SWOT of the AC, the results of this research can pave the way for policy makers and planners in this field.

The purpose of this study is to present an alternative to university ranking lists published in U.S. News & World Report, Times Higher Education, Academic Ranking of World Universities and Money Magazine. A strategy is proposed to mine a collection of university data obtained from Twitter and publicly available online academic sources to compute social media metrics that approximate typical academic rankings of US universities.

The Twitter application programming interface (API) is used to rank 264 universities using two easily collected measurements. The University Twitter Engagement (UTE) score is the total number of primary and secondary followers affiliated with the university. The authors mine other public data sources related to endowment funds, athletic expenditures and student enrollment to compute a ranking based on the endowment, expenditures and enrollment (EEE) score.

In rank-to-rank comparisons, the authors observed a significant, positive rank correlation (τ = 0.6018) between UTE and an aggregate reputation ranking, which indicates UTE could be a viable proxy for ranking atypical institutions normally excluded from traditional lists.

The UTE and EEE metrics offer distinct advantages because they can be calculated on-demand rather than relying on an annual publication and they promote diversity in the ranking lists, as any university with a Twitter account can be ranked by UTE and any university with online information about enrollment, expenditures and endowment can be given an EEE rank. The authors also propose a unique approach for discovering official university accounts by mining and correlating the profile information of Twitter friends.