Literature shows that organisational identification has important implications in employee performance and their intention to leave a firm. In this paper, we explore the differential implications of employee identification in settings where the employees are employed by one firm but represent client firms in their work. Specifically, the paper investigates how employee identification with the firm that employs them as opposed to the client firm impact their work outcomes such as performance, job satisfaction and intention to leave. Findings from a survey of employees in an off-shored call centre show employee identification with the firm is as important as identification with the client since they develop specific affect for both the organisations that impact their work outcomes. They also foster different outcomes, e.g., intention to leave is affected by identification with the employing firm, while performance is affected by identification and job satisfaction is impacted by both kinds of identifications.

Purpose Much of what we learn from empirical research is based on a specific empirical model(s) presented in the literature. However, the range of plausible models given the data is potentially larger, thus creating an additional source of uncertainty termed: model uncertainty. The purpose of this paper is to examine the effect of model uncertainty on empirical research in HRM and suggest potential solutions to deal with the same. Design/methodology/approach Using a sample of call center employees from India, the authors test the robustness of predictors of intention to leave based on the unfolding model proposed by Harman et.al. (2007). Methodologically, the authors use Bayesian Model Averaging (BMA) to identify the specific variables within the unfolding model that have a robust relationship with turnover intentions after accounting for model uncertainty. Findings The findings show that indeed model uncertainty can impact what we learn from empirical studies. More specifically, in the context of the sample, using four plausible model specifications, the authors show that the conclusions can vary depending on which model the authors choose to interpret. Furthermore, using BMA, the authors find that only two variables, job satisfaction and perceived organizational support, are model specification independent robust predictors of intention to leave. Practical implications The research has specific implications for the development of HR analytics and informs managers on which are the most robust elements affecting attrition. Originality/value While empirical research typically acknowledges and corrects for the presence of sampling uncertainty through p -values, rarely does it acknowledge the presence of model uncertainty (which variables to include in a model). To the best of the authors’ knowledge, it is the first study to show the effect and offer a solution to studying total uncertainty (sampling uncertainty + model uncertainty) on empirical research in HRM. The work should open more doors toward more studies evaluating the robustness of key HRM constructs in explaining important work-related outcomes.

The primary purpose of this article is to demonstrate the execution of a successful short-term study trip to Southeast Asia and its influence on a student's cultural intelligence. This article discusses an academic component of an international study trip that was developed for sophomores at a private university in the New England region of the United States. In an attempt to internationalize, the university led students on a 2-week international trip to Malaysia and Singapore known as the Sophomore International Experience. The authors have developed a model that combines an academically rigorous curriculum that juxtaposes domestic events/experiences with those of the foreign country and propose that the trip gives students first-hand international experience that prepares them to develop a global perception. The article evaluates the validity of the proposed theory with the help of the Cultural Intelligence Scale that measures significance improvements in cultural intelligence after taking the trip.

This conceptual paper looks at dynamic capabilities as a specific type of knowledge that is geographically localized. Dynamic capabilities are knowledge-based processes that are developed over time by means of interactions among a firm’s resource bundles and capabilities. Dynamic capabilities enhance a firm’s capacity to leverage resources and organizational processes to increase profitability. Corporate headquarters were selected as a unit of analysis because of their knowledge-intensive nature. Empirical evidence suggests that just over 5% of headquarters relocate every year and that the reasons for the relocations go beyond tax incentives. It is argued that the geographical proximity of headquarters causes spillover of operational knowledge during interactions between managers. This operational knowledge includes various routines and contains dynamic capabilities. This paper links studies on dynamic capabilities and studies on geography of knowledge and headquarter relocations. The information gathered can help to explain why corporate headquarter relocations take place, and how firms may increase profitability by moving their headquarters to a location favorable to building particular dynamic capabilities.

IntroductionIn strategic management, firms create competitive advantage either by picking or building capabilities. Those capabilities that are firm-specific can be sources of advantage, and as such they should be built up, organized and protected. This approach is called 'dynamic capabilities' in order to emphasize the exploitation of existing internal and external company-specific competencies to address changing environments (Teece et al., 1997). The framework is based on the development of managerial competencies and difficult-to-imitate mixtures of executive, functional and technological skills. It also integrates and draws on research in administration of RD Constance, 1997; Eisenhardt and Martin, 2000; and Blyler and Coff, 2003). Dynamic capabilities have been found to represent a specific type of knowledge (Makadok, 2001; and Malik and Kotabe, 2009). However, further implications that derive from the knowledge aspect of dynamic capabilities have not been analyzed. For instance, one of the key attributes of knowledge, according to numerous studies, is geographical-localization that implies that knowledge flourishes in specific locations (Jaffe et al., 1993; Zucker et al., 1998a; and Keller, 2002). Therefore, dynamic capabilities, being a special type of knowledge, must be geographically bounded.The knowledge-intensive nature of headquarters makes them a perfect place to store a large portion of dynamic capabilities, and an interesting subject for study. Traditional functions of headquarters include being a major source of knowledge and competencies (Ambos et al., 2006). This paper aims at analyzing the evolution of the notion of dynamic capabilities and its associated concepts, arguments about the geographical localization of knowledge and analysis of knowledge networks.In the strategic management field, it is suggested that firms create economic rents by means of two separate fundamental mechanisms: (1) resource-picking; and (2) capability-building. While employing resource-picking mechanisms, executives collect information and perform analyses to outmaneuver the resource marketplace in selecting resources. This approach is analogous to the technique used by mutual fund managers who seek to outsmart the stock market in selecting securities. While employing capability-building mechanisms, executives plan and build organizational systems to improve the output of any the company acquires. These two rent-producing approaches are not mutually exclusive, and in many cases firms employ both of them either consciously or unconsciously. One of the examples of simultaneous use of two rent-producing mechanisms is the relocation of corporate headquarters. Headquarter relocation can be viewed as both a resource-picking and a capability-building mechanism (Figures 1 and 2).Research on the interaction between these two rent-producing methods revealed that the two mechanisms are complementary in some situations, but substitutes in others (Richard, 2001). The basic assumption is that firms produce a sequence of 'temporary' advantages by adding and reconfiguring resources, which may develop into a sustained advantage once the full pattern is considered. This process allows the company to obtain higher rent by achieving new forms of competitive advantage (Carmeli and Tishler, 2004). Higher rent is a rate of return generated in excess of the minimum needed to attract resources (Milgrom and Roberts, 1992). Dynamic capabilities are treated as a special type of knowledge, and defined as firm-specific capabilities that can be sources of advantage by exploiting existing internal and external company-specific competencies to address changing environments (Teece et al. …

In the context of an increasing importance of emerging markets in firms’ international strategies, this paper contributes to the still little researched topic of selection criteria used for international expansion when selecting among emerging markets. The existing literature on both International Market Selection (IMS) and emerging markets are reviewed in order to identify potentially important selection criteria. These criteria are then tested on a sample of professionals with work experience in business development functions at companies based in France. The results of the study indicate that 8 out of the 11 tested criteria are of major importance in IMS. One of these shortlisted criteria is less relevant for emerging markets, but another criterion not considered important in general is found relevant for emerging markets, constituting again a list of eight criteria that were identified as important when selecting a target among a group of emerging markets. Drawing on these findings, implications for managers with different kinds of responsibilities were identified to help them in the IMS process.

Private equity is an important source of financing for French companies. This paper examines the relationship between private equity and the competitiveness of buyout firms in a French context. Prior literature has assessed private equity markets and emphasized mechanisms including the replacement or reorganization of management, the reduction of agency costs, the financial pressure through leverage, the influence of shareholders and the management expertise of the fund. However, as the majority of these existing studies focus on private equity in the U.S. and U.K., little consensus has been achieved about the application of these results to France. In this paper, we discuss the mechanisms of private equity in a French context. We analyze the criteria on which buyout companies are chosen by funds, as well as the relationship between private equity and subsequent firm performance. Our findings show that French private equity funds select companies that, in comparison to their competitors, are larger in size and are better performers. Our results also show that following a buyout, companies do not experience a significant performance improvement. Based on our empirical analysis, we find no significant evidence that French private equity creates long-term value.

Technological and innovation capabilities play an important role in determining the performance of firms, especially in knowledge intensive industries. Despite the plethora of studies testing the relationship between innovation capabilities and firm performance, little consensus has been achieved on the veracity of the theoretical claims. In this paper, we argue that the lack of consensus could be on account of the failure to take into account the endogeneity that arises from the decision process that underlies the relationship between development of technological capabilities and its impact on firm performance. We address both these issues and demonstrate that alternative empirical designs can help provide greater external validity.

We demonstrate the effect of ignoring the role of heteroskedasticity modelling in applied corporate finance studies and show that it may have important consequences in corporate financial decisions. In this paper, we specifically focus on the effect of heteroskedasticity on the factors affecting the open market operations of the firm. We show that in the absence of modelling heteroskedasticy results from prior research are consistent. By explicit modelling of heteroskedasticity some results are reversed. In particular, we find that the effect of key variables such as dividends, leverage and the likelihood of takeover on the probability of repurchase differs after controlling for heteroskedasticity.

The method of specifying models through regressions can often depict an incomplete picture due to the assumption that inference is conditional upon the specification(s) being an accurate description of the true data generating process. Studies have shown that perfect foresight on the true data generating process is a tenuous argument, especially since knowledge in various sub-fields of management is relatively eclectic with considerable variation in results from empirical research. We demonstrate that Bayesian Model Averaging BMA could be an effective mechanism to eliminate model uncertainty and produce reliable inference and apply it to the domain of attrition research.

This study examines relation between equity returns and fundamental variables by utilizing multifactor asset pricing models. Specifically it incorporates several variables from prior empirical research to examine impact of systematic risk on equity returns in financial sector. The empirical results show that explanatory power of systematic risk varies by models, but a positive relationship between systematic risk and returns is consistent. At same time, study reveals a significant relationship between equity returns and market value, book-to-market equity, earnings yield, leverage factors, sales-to-price ratio, book value per share, and earnings per share.(ProQuest: ... denotes formulae omitted.)IntroductionThe recent turmoil of global equity market has once again emphasized importance of accurate forecasting of asset returns and cost of capital, as rates of return are fundamental units that financial analysts and portfolio managers use for making investment decisions. Along with traditional systematic risk beta (?), prior research has suggested other factors such as Price-to-Earnings (P/E) ratio and size of a company among others in predicting stock returns. For instance, it has been shown that value stocks (firms with a low P/E) and small size tend to outperform growth stocks (high P/E) and large firms (CFA, 2010a).While several empirical regularities have been unearthed by prior research, much of research in this area did not focus on understanding key drivers of returns in financial sector. This study aims to address these lacunae in literature. More specifically, it examines key drivers of returns for financial firms across different multifactor asset pricing models. This paper differs from other studies and offers its unique contribution in subject matter. First, it investigates issue utilizing data from a specific sample of firms in financial sector of US market. Companies in this sector, including those in diversified financial industry, possess different characteristics from other industries in equity market. Specifically, firms in financial sector tend to have higher leverage than others. Research shows that these firms have greatest percentage of liabilities-to-total assets (80.50%) as compared to those in other industries (CFA, 2010b). High leverage is normal for financial firms, while such characteristics more likely reflect financial distress in case of firms that do not operate in financial sector. Therefore, most research that spans across multiple industries choose to exclude financial firms due difference in their characteristics. This leads to very little empirical work concentrating on financial sector in this subject matter. Because this study includes only financial firms in dataset, it is able to look deeper into diversified financial industry without contamination on account of difference between financial firms and non-financial ones.Secondly, paper compares across several empirical multifactor asset pricing models that have been used to determine larger set of factors that predict stock returns in other industries. This exercise is undertaken as prior research has not arrived at a consensus on role of various factors that drive asset returns. It is argued that this can be on account of using different dataseis spanning different time frames. Thus, in this case, paper subjects same dataset across same time frame to host of models to check for robustness of observed outcomes.The financial factors used to estimate expected returns are important to successful investment decision. As Black (1995) states, the key issue in investments is estimating expected return. Accordingly, results of this study can be converted into a practical investment tool to estimate expected returns by running regression models of returns on select factors. …

Employee turnover remains to be one of the biggest human resource problems facing the Indian international call center industry. This paper aims to provide a comprehensive study of how the attitudes of call center employees toward different aspects of their work affect their intention to leave. Our specific contribution to the literature is in understanding the heterogeneity among employees and how this affects meaningful inference in studying employees' intention to leave. To achieve this goal, we compare and contrast between traditional ordinary least squares regression models that have been used in the extant literature with latent class analysis. Latent class analysis suggests the presence of three distinct groups of employees, thus confirming the heterogeneity present in the data. The three groups can be represented as the two polar groups, one keen on staying and the other keen on leaving, and a significantly large third group of employees who are unsure. We also find that the impact of different attitudes vary between groups in terms of both economic significance (magnitude of coefficients), and statistical significance. This study throws important light on the research on turnover and has significant research and practical implications.

This study examines the relationship between various dimensions of a firm’s technological innovation capabilities and its international performance. We use panel data with multiple indicators of firm level technological capabilities including generation, dissemination, strength and speed of innovation. We employ a quantile regression analysis which allowed us to test the impact of innovation capability on international performance of high, average and poor performers. Our empirical findings indicate significant disparity between the ordinary least square and quantile regression results.

Stress is one of the biggest human resource (HR) problems facing high turnover industries like the Indian international call centre industry. This paper provides a comprehensive study of how the attitudes of call centre employees towards different aspects of their work affect their level of stress experienced. Our specific contribution to the literature is in understanding the heterogeneity among employees and how that affects meaningful inference in studying employees’ perceptions of stress. To achieve this goal, we compare and contrast between traditional regression models used in the extant literature with latent class regression analysis. The latent class analysis suggests the presence of four distinct groups of employees, confirming the heterogeneity present in the data. This study is unique in trying to explore how individuals may differ in their experience of stress and how there may be heterogeneity in the relationships explored between various cognitive and affective variables and experiences of stress.

Most studies that use classical unit-root tests in OECD countries support the unemployment hysteresis hypothesis. However, similar classical tests performed on US data yield mixed results, uncovering specification issues. This study uses a number of panel unit root tests, which are known to overcome specification problems, to check the existence of hysteresis in unemployment data from three Massachusetts regions. The empirical results strongly reject a unit root in the unemployment rates, refuting the unemployment hysteresis hypothesis.

Growth economists still face major challenges and limitations to incorporate institutions into the standard growth framework. This article develops a simple institutions-augmented Solow growth model --that can be used in the classroom and for policy discussions --that accounts for the interactions between institutions and factor-productivity and examine the impacts of the quality of institutions on levels and growth rates of output. The institutions-augmented growth model shows that differences in the quality of institutions preclude income convergence and determine both the level and the growth rate of output per worker. The model also shows that poor institutions induce poverty traps. Furthermore, the income gap between rich and poor countries will not disappear if poor countries’ institutions do not improve relative to their rich counterpart.

The phenomenon of outsourcing has engulfed the accounting industry and offers a wide range of services from bookkeeping, accounts payable, debt collection, invoicing, to tax return preparation. As companies become more comfortable with the services provided by outsourcing facilitators, the level of outsourcing in the accounting industry will increase to allow U.S. firms to focus on higher margin services and meet client demands in more technical areas of tax, estate, and retirement planning. Through a survey and data collection primarily focused on three areas: outsourcing drivers, concerns stakeholders have about outsourcing, and the perceptions about the offshorability of specific functions, the study concludes that firms are engaging in outsourcing activities, and that those firms who do outsource work realize benefits in and ease their perceptions about doing so. Firms who outsource have been able to cut costs and increase staff. These same firms also are less concerned about most of the issues (privacy, client relationships, etc) which may be as a result their outsourcing activities. The firms also have a higher perception of the outsourcibility of most of the functions in the accounting industry. The study further suggests policy implications concerning all stakeholders in the accounting industry: students, professors, accounting professionals and firms, regulatory bodies, and politicians.

This study utilises eight alternative measures of institutions and the instrumental variable method to examine the impacts of institutions on poverty. The estimates show that an economy with a robust system to control corruption, an effective government, and a stable political system will create the conditions to promote economic growth, minimise income distribution conflicts, and reduce poverty. Corruption, ineffective governments, and political instability will not only hurt income levels through market inefficiencies, but also escalate poverty incidence via increased income inequality. The results also imply that the quality of the regulatory system, rule of law, voice and accountability, and expropriation risk are inversely related to poverty but their effect on poverty is via average income rather than income distribution.