Gender differences in evaluation of new business opportunity: A stereotype threat perspective

This study draws on stereotype threat theory to explore differences between men and women on evaluation of new business opportunities. Two controlled experiments, one with business students in Turkey and another with working professionals in the United States, were conducted. Participants were randomly assigned to specific experimental conditions and their assessment of a new business opportunity was measured after presentation of stereotypical information. As predicted, men reported higher opportunity evaluation than women when no gender stereotypical information was presented, whereas men and women evaluated the business opportunity equally favorably when entrepreneurs were described using gender-neutral attributes. Interestingly, gender differences in opportunity evaluation were exacerbated when entrepreneurship was linked to masculine stereotypical information, and reversed in favor of women when entrepreneurship was linked to feminine stereotypical information. Practical implications and directions for future research are discussed.     

Capital Inflows and House Prices: Aggregate and Regional Evidence from China

Rising house prices in China have been of concern for investors and policymakers. Prices have risen substantially in the last decade, especially in large urban cities, and some economists have expressed concerns about the affordability of residential housing for young adults. This phenomenon becomes a major concern for policymakers, in terms of managing policies to balance the residential needs of individuals and the transition to a market economy. Theoretically, house prices ought to be linked to economic factors such as disposable income, availability of land to build and credit policy. However, it appears that traditional economic theories fail to appropriately explain house prices in China. We provide an explanation from the perspective of capital inflows into China. In terms of per capita remittances, China receives the highest inflow of foreign capital, and this may have a significant impact on risk adjusted returns in the Chinese market. To investigate this relationship, we use the vector error correction model to assess the impact of capital inflows on house prices. We find that capital inflows have a significant positive effect on house prices. The study makes important contributions to understanding the relationship between house prices and foreign remittances after controlling for other economic factors. China is a large economy. Because the impact of economic development in China has not been consistent across the country, we address the regional differences in the house price changes to capital inflows. Using regional data, we show that capital inflows have an asymmetric effect on the housing market across different provinces and cities of China. This has important implications for the development of economic policies in China that aim to provide fair access to residential housing for everyone. These findings are also relevant to investors in the housing market, whether investing for a personal residential home or as part of their diversified investment portfolio. It will also be informative to see how a reversal of capital inflows associated with tighter financing conditions in advanced countries will affect house prices in China.     

An empirical investigation of the effect of imputation credits on remittance of overseas dividends

Overseas dividend remittance is an important vehicle for multinational corporations (MNCs) to move funds among their global subsidiaries. Using firm-level data from 2001 to 2004 for Taiwan-based MNCs with subsidiaries in China, this paper provides empirical evidence on the effect of imputation credits on overseas dividend remittances. We find that imputation credits have a positive effect on increasing foreign dividend payouts, thereby reducing the efficiency loss induced by the tax cost for within-firm dividends of MNCs. We also document evidence that parent companies’ net fund flows from related-party transactions with their subsidiaries are negatively correlated with dividends repatriated from those affiliates, supporting the notion that transfer-pricing may be substituting for within-firm dividend remittance. Our results contribute to understanding the links between taxation and related-party transactions and subsidiary dividend repatriation decisions of MNCs.     

The Time-Series Properties of House Prices: A Case Study of the Southern California Market

We examine the time-series relationship between house prices in eight Southern California metropolitan statistical areas (MSAs). First, we perform cointegration tests of the house price indexes for the MSAs, finding seven cointegrating vectors. Thus, the evidence suggests that one common trend links the house prices in these eight MSAs, a purchasing power parity finding for the house prices in Southern California. Second, we perform temporal Granger causality tests. The Santa Anna MSA temporally causes house prices in six of the other seven MSAs, excluding only the San Luis Obispo MSA. The Oxnard MSA experiences the largest number of temporal effects from six of the seven MSAs, excluding only Los Angeles. The Santa Barbara MSA proves the most isolated. It temporally causes house prices in only two other MSAs (Los Angeles and Oxnard) and house prices in the Santa Anna MSA temporally cause prices in Santa Barbara. Third, we calculate out-of-sample forecasts in each MSA, using various vector autoregressive and vector error-correction models, as well as Bayesian, spatial, and causality versions of these models with various priors. Different specifications provide superior forecasts in the different MSAs. Finally, we consider how theses time-series models can predict out-of-sample peaks and declines in house prices after in 2005 and 2006. Recursive forecasts, where we update the sample each quarter, provide reasonably good forecasts of the peaks and declines of the house price indexes.     

Organizational differences,relational mechanisms,and alliance performance

In studying the antecedents of alliance performance, one stream of research has underscored the alignment between partners' characteristics whereas another has concentrated on relational mechanisms such as mutual trust, relational embeddedness, and relational commitment. We integrate these two perspectives by examining how congruence of the partners' cultures and organizational routines facilitates the emergence of relational mechanisms in non‐equity alliances. Our analysis of 420 non‐equity alliances in the information technology industry demonstrates how differences in partners' internal task routines undermine relational mechanisms that in turn impact alliance performance. Partners who acknowledge their latent differences can overcome some of these negative consequences. We advance alliance research by studying the performance implications of alliance partners' organizational differences and by demonstrating how these effects are mediated by relational mechanisms. Copyright © 2012 John Wiley & Sons, Ltd.     

Structural interdependence within top management teams: A key moderator of upper echelons predictions

Studies of the effects of top management team (TMT) composition on organizational outcomes have yielded mixed and confusing results. A possible breakthrough resides in the reality that TMTs vary in how they are fundamentally structured. Some are structured such that members operate independently of each other, while others are set up such that roles are highly interdependent. We examine the potential for three facets of structural interdependence—horizontal, vertical, and reward interdependence—to resolve ambiguities regarding effects of TMT heterogeneity. Based on a sample of TMTs in technology firms, we find that the three facets of structural interdependence are potent moderators of two classic predictions: the positive association between TMT heterogeneity and member departures, and between TMT heterogeneity and firm performance. Copyright © 2014 John Wiley & Sons, Ltd.     

The effects of public expenditures on labour productivity in Europe

Empirica - In this paper, we analyse the effects of public expenditures and their structure on productivity growth in industry and services in the European Union (EU) countries (1996–2017)....     

Modeling Drivers and Barriers of Artificial Intelligence Adoption: Insights from a Strategic Management Perspective

Artificial intelligence (AI) in business processes and academic research in AI has significantly increased. However, the adoption of AI in organizational strategy is yet to be explored in extant literature. This study proposes two conceptual frameworks showing hierarchical relationships among the various drivers and barriers to AI adoption in organizational strategy. In a two-step approach, the literature study is first done to identify eight drivers of and nine barriers to AI adoption and validated by academic and industry experts. In the second step, MICMAC (matrice d'impacts croises-multiplication appliqúe a un classment or cross-impact matrix multiplication applied to classification) analysis categorizes the drivers and barriers to AI adoption in organizational strategy. Total interpretive structural modeling (TISM) is developed to understand the complex and hierarchical associations among the drivers and barriers. This is the first attempt to model the drivers and barriers using a methodology like TISM, which provides a comprehensive conceptual framework with hierarchical relationships and relative importance of the drivers and barriers to AI adoption. AI solutions' decision-making ability and accuracy are the most influential drivers that influence other driving factors. Lack of an AI adoption strategy, lack of AI talent, and lack of leadership commitment are the most significant barriers that affect other barriers. Recommendations for senior leadership are discussed to focus on the leading drivers and barriers. Also, the limitations and future research scope are addressed.     

Normative influence and masstige purchase intention: Facilitators,inhibitors, and the moderating effect of celebrity endorsement

Masstige marketing has gained considerable attention in the recent past as a theoretically significant and practically relevant concept. Masstige strategy encompasses all those activities directed to position the products for the masses, neither by offering drastic price reductions nor discounts. Rather its success depends on product innovation and promotion. Although it has been recognized as an important strategic construct, the nascent concept needs further investigation for better understanding. This research identifies significant gaps in the extant literature on fashion accessories masstige brands and intends to bridge them. The objective of the current study is to empirically investigate the factors that facilitate or inhibit masstige purchase intentions. Our study uncovers the role of normative influence in influencing the purchase intentions of a masstige fashion accessory brand, that is, Armani Exchange. Data were collected from 395 respondents, and structural equation modeling was applied to check the proposed hypotheses. The study's results revealed that conspicuous and social values play an important role as facilitators. In addition, the study highlighted that masstige brands need to overcome inhibitors like identity avoidance and deficit-value avoidance to develop masstige purchase intention. Moderation analysis highlighted the significant influence of celebrity endorsement in strengthening the facilitators and overcoming inhibitors associated with masstige purchase intention. The study's results can help marketers to position their masstige brands by adopting the right strategies that can be formulated by taking into account the influence of stimulus, facilitators, inhibitors, and a moderating variable examined in the study.     

Persistence of economic uncertainty: a comprehensive analysis

One of the most heavily researched and cited issue in applied economics is the relationship of uncertainty indices with the financial and macroeconomic variables. While the statistical features of financial and macroeconomic variables have been thoroughly examined, virtually nothing has been done to examine uncertainty indices under the statistical perspective. In this paper, we focus on two primary characteristics of uncertainty indices: persistence and chaotic behaviour. In order to evaluate the persistence and the chaotic behaviour we analyse 72 popular uncertainty indices constructed by forecasting models, text mining from news articles and data mining from monetary variables to measure the Hurst and Lyapunov exponents in rolling windows. The examination in rolling windows provides a dynamic evaluation of the specific characteristics revealing significant variations of persistence and chaotic dynamics with time. More specifically, we find that almost all uncertainty indices are persistent, while the chaotic dynamics are detected only sporadically and for certain indices during recessions of economic turbulence. Thus, we suggest that the examination of persistence and chaos should be a prerequisite step before using uncertainty indices in economic policy models.