The soft side of knowledge transfer partnerships between universities and small to medium enterprises: an exploratory study to understand process improvement

Abstract

The study explores the soft side of knowledge transfer partnerships between universities and small to medium enterprises (SMEs), a topic which is often neglected in the knowledge management literature. The aim of this paper is to uncover the issues which emerge during formation of a partnership between heterogeneous organizations and universities. In addition, the study unfolds the criticalities of typical process improvement capability that supports the knowledge transfer partnerships between universities and SMEs. Using multiple cases, this study unravels the dominant elements that influence knowledge transfer process development, governance, implications and responsibilities. The major contribution of this study is the development of a framework based on empirical evidence using three knowledge transfer partnerships (KTPs) which illustrates the way in which soft factors in knowledge transfer partnership phases may have an impact on success or failure of university–industry collaborations for innovation.     

Study and analysis of occupational risk factors for ergonomic design of construction worksystems

Manual material handling (MMH) is unavoidable because of the nature of jobs or tasks as and man-machine interfaces in a construction worksystem. Data were collected from six strata of workers viz., masons, mason helpers, carpenters, welders, gas cutters and ground-level helpers (259 out of 700 workers) from a construction site of a steel plant located in India to analyze different types of occupational risk factors, such as awkward posture, repetitive movements and others associated with MMH activities to assess their impact on musculoskeletal disorders (MSDs). It is essential that these risk factors are required to be under control through application of ergonomics-based design approaches for construction worksystem. In this context, multinomial logistic regression analyses were used to identify the significant risk factors among the workers. The results shows that masons, mason helpers, carpenters, welders/gas cutters and ground-level helpers are greatly affected by static body posture, type of tools used, excessive stress due to repetition, awkward postures and extreme climate, respectively. Appropriate preventive and corrective measures are suggested for minimization of risks associated with such jobs/tasks to improve health and performance of the workers.     

On a modified version of intervened negative binomial distribution

In this paper, a generalized version of the intervened negative binomial distribution of Kumar and Sreeja [On intervened negative binomial distribution and some of its properties. Statistica. 2012;72:395–404] is considered and studied some of its properties. Certain methods of estimation of the parameters of the distribution are discussed and illustrated with the help of real life data sets. A test procedure is suggested for testing the intervention parameter and a simulation study is conducted for examining the performance of the estimators.     

Classification into two normal populations with a common mean and unequal variances

The problem of classification into two univariate normal populations with a common mean is considered. Several classification rules are proposed based on efficient estimators of the common mean. Detailed numerical comparisons of probabilities of misclassifications using these rules have been carried out. It is shown that the classification rule based on the Graybill-Deal estimator of the common mean performs the best. Classification rules are also proposed for the case when variances are assumed to be ordered. Comparison of these rules with the rule based on the Graybill-Deal estimator has been done with respect to individual probabilities of misclassification.     

Design and analysis of mixture experiments with process variable

A mixture experiment is an experiment in which the response is assumed to depend on the relative proportions of the ingredients present in the mixture and not on the total amount of the mixture. In such experiment process, variables do not form any portion of the mixture but the levels changed could affect the blending properties of the ingredients. Sometimes, the mixture experiments are costly and the experiments are to be conducted in less number of runs. Here, a general method for construction of efficient mixture experiments in a minimum number of runs by the method for projection of efficient response surface design onto the constrained region is obtained. The efficient designs with a less number of runs have been constructed for 3rd, 4th, and 5th component of mixture experiments with one process variable.     

DO TERRORIST ATTACKS IMPACT EXCHANGE RATE BEHAVIOR? NEW INTERNATIONAL EVIDENCE

This study examines whether terrorist attacks affect bilateral exchange rates. Using historical 10‐minute exchange rate data for 21 countries' currency vis‐à‐vis the U.S. dollar, we show that exchange rate returns of all countries are statistically significantly affected by terrorist attacks. Some exchange rates appreciate and some depreciate following a terrorist attack, some currencies experience exchange rate reversals while others experience a persistent effect. Generally, the effect declines but persists as terrorist attacks become stale information. (JEL F31, F37)     

Managing Retail Budget Allocation between Store Labor and Marketing Activities

The performance of a retail store depends on its ability to attract customer traffic, match labor with incoming traffic, and convert the incoming traffic into sales. Retailers make significant investments in marketing activities (such as advertising) to bring customers into their stores and in‐store labor to convert that traffic into sales. Thus, a common trade‐off that retail store managers face concerns the allocation of a store's limited budget between advertising and labor to enhance store‐level sales. To explore that trade‐off, we develop a centralized model to allocate limited store budget between store labor and advertising with the objective of maximizing store sales. We find that a store's inherent potential to drive traffic plays an important role, among other factors, in the relative allocation between advertising and store labor. We also find that as advertising instruments become more effective in bringing traffic to stores, managers should not always capitalize this effectiveness by increasing their existing allocations to advertising. In addition, we discuss a decentralized setting where budget allocation decisions cannot be enforced by a store manager and present a simple mechanism that can achieve the centralized solution. In an extension, we address the budget allocation problem in the presence of marketing efforts to shift store traffic from peak to off peak hours and show that our initial findings are robust. Further, we illustrate how the solution from the budget allocation model can be used to facilitate store level sales force planning/scheduling decisions. Based on the results of our model, we present several insights that can help managers in budget allocation and sales force planning.     

The hunt for a cure for Parkinson's disease

Several exciting new scientific advances have been made in the past decade toward both understanding the causes of and finding a cure for Parkinson's disease. Heartened by an acceleration in research findings in the past several years, the government has recently called for an infusion of funds from both the National Institutes of Health and private foundations into this burgeoning area of biomedical research. Most currently available conventional treatments for the disease only temporarily delay symptom presentation while doing nothing to halt disease progression. However, the rapidly accelerating pace of research in this field has left researchers hopeful that Parkinson's will be the first major age-related neurodegenerative disease for which we have a viable cure. In this article, advances in various areas of Parkinson's disease research are reviewed.     

Short- and long-run rolling causality techniques and optimal window-wise lag selection: an application to the export-led growth hypothesis

The literature devoted to the export-led growth (ELG) hypothesis, which is of utmost importance for policymaking in emerging countries, provides mixed evidence for the validity of the hypothesis. Recent contributions focus on the time-dependence of the relationship between export and output growth using rolling causality techniques based on vector autoregressive models. These models focus on a short-term view which captures single policy-induced developments. However, long-term structural changes cannot be covered by examinations related to the short-term. This paper hence examines the time-varying validity of the ELG hypothesis for India for the period 1960–2011 using rolling causality techniques for both the short-run and long-run horizon. For the first time, window-wise optimal lag-selection procedures are applied in connection with these techniques. We find that exports long-run caused output growth from 1997 until 2009 which can be seen as a consequence of political reforms of the 1990s that boosted economic growth by generating foreign direct investment opportunities and higher exports. For the short-run, export significantly caused output in the period 1998–2003 which followed a concentration of liberalization measures in 1997. Causality in the reversed direction, from output to exports, only seems to be relevant in the short-run.