Exploitative and exploratory innovations in emerging economies: The role of realized absorptive capacity and learning intent

This paper investigates the mediating effect of learning intent in transforming local suppliers’ potential absorptive capacity into realized absorptive capacity and its impact on exploitative and exploratory innovation. Using survey data from 155 auto parts manufacturers in Pakistan, we find that local firms’ realized absorptive capacity enables them to develop both exploitative and exploratory innovations. The findings further suggest that local suppliers’ learning intent mediates the relationship between potential and realized absorptive capacity which in turn lead to both types of innovation. In the context of the emerging economy of Pakistan, local suppliers’ absorptive capacity is found to be critically important in spurring exploitative and exploratory innovation, but learning intent enables realized absorptive capacity and thus in conjunction with realized absorptive capacity supports innovation. Consequently, there would be a strong case for policy intervention to assist emerging economy firms in building their absorptive capacity and strengthening their learning intent as a route for promoting innovation and improving their value added position in the global value chains of multinational enterprises.     

Benchmarking sales staffing efficiency in dealerships using extended data envelopment analysis

This study presents an approach to benchmark dealer performance in a business-to-business setting through a rigorous efficiency analysis of sales staff allocation. Using a series of basic and extended data envelopment analysis (DEA) models on data collected from a survey of self-reported financial and statistical information, this research assesses dealer efficiency and compares the efficiency scores to traditional financial benchmarking. Findings support the minimization of outsourcing services that are customer interactive and highly specific to a transaction to differentiate the dealer from its competition. Integrating the results from DEA models, manufacturers obtain a comprehensive view of allocating sales staff to increase dealer efficiency and generating a complementary approach to traditional financial ratio benchmarking in determining best practices to other dealers.     

Big data: Dimensions,evolution, impacts,and challenges

Big data represents a new technology paradigm for data that are generated at high velocity and high volume, and with high variety. Big data is envisioned as a game changer capable of revolutionizing the way businesses operate in many industries. This article introduces an integrated view of big data, traces the evolution of big data over the past 20 years, and discusses data analytics essential for processing various structured and unstructured data. This article illustrates the application of data analytics using merchant review data. The impacts of big data on key business performances are then evaluated. Finally, six technical and managerial challenges are discussed.     

Making use of quantitative content analysis: Insights from academia and business practice

This article features a moderated conversation between the author and five leading researchers and practitioners in the field of quantitative content analysis and, more specifically, computer-aided textual analysis (CATA). The interview subjects discuss the factors contributing to CATA’s rise as a research method as well as the benefits and pitfalls of using CATA. The conversation also covers best-practice advice that companies may employ to increase the accuracy of CATA results. These include using different programs or algorithms for the same problem, known as algorithm error.     

我国企业组织冲突的原因思考及应对策略

经济活动主体的机会主义行为倾向构成了组织冲突发生的必然原因 ;人的有限理性为机会主义的产生奠定了基础 ,因而也进一步增加了组织冲突发生的可能性。企业组织冲突管理始终是企业管理中的一项重要内容 ,企业组织应突破传统的冲突管理观念 ,从管理哲学的高度超越冲突 ,走理性与非理性相结合的冲突管理道路。     

Testing for convergence in bank efficiency: a cross-country analysis

This paper empirically investigates a possible convergence among the operational efficiency of financial institutions across countries. We explore (i) the relative performance of banking industries in two samples (European and global) over time, and (ii) whether banking industries are likely to attain the same level of efficiency in the long run as implied by international financial integration. We find that convergence in bank efficiency is incomplete and limited to European banking industries. Differing level of bank efficiencies across the globe may offer opportunities for international investors who would like to capitalize on such market imperfections. Our findings also have implications for policy makers who are concerned with the full integration and the stability of the global financial system.     

An efficiency and effectiveness model for international tourist hotels in Taiwan

Taiwan's economic growth has improved the quality of life and raised the standard of the tourism industry in Taiwan. This paper selects the hotel industry, in order to assess how international tourist hotels operate their business by applying data envelopment analysis (DEA) to measure their operational efficiency and effectiveness. By using the DEA model to assess the results of the relative efficiency and effectiveness of hotels to improve their operations, the paper also aims to rank the hotels by applying the VlseKriterijumska Optimizacija I Kompromisno Resenje method combined with entropy weight among the criteria.     

Click Here for a Data Scientist: Big Data,Predictive Analytics,and Theory Development in the Era of a Maker Movement Supply Chain

Predictive analytics is impacting many diverse areas, ranging from baseball and epidemiology to forecasting and customer relationship management. Manufacturers, retailers, software companies, and consultants are creatively discovering new applications of big data using predictive analytics in supply chain management and logistics. In practice, predictive analytics is generally atheoretical; however, we develop a 2 × 2 model to explain the role of predictive analytics in the theory development process. This 2 × 2 model shows that in our discipline we have traditionally taken one path to theory development, but that predictive analytics can be a salient component of a comprehensive theory development process. The model points to a number of research questions that need to be addressed by our research community. These questions are not just highly relevant to the academic community but also in urgent need of answers to help practitioners execute the right strategies with greater precision and efficiency. We also discuss how one disruptive trend, the maker movement, changes the nature of who the producers are in the supply chain, making big data even more valuable. As we engage in higher levels of dialogue we will be able to make meaningful progress addressing these vital research topics.