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Women in many countries are breaking through the gender barrier and are working in positions where they have a major impact on the buying and selling activities in business-to-business relationships. A number of studies have investigated the role gender plays in driving perceptions of sales representatives in the USA, however, little research has been undertaken on this important topic in China, one of the largest and most influential countries. Consequently, the purpose of this study is to examine whether the gender of both the buyer and seller, affects perceptions of expertise, trust and loyalty in business relationships.

A survey instrument was developed, tested and used on individuals with purchasing responsibility in China. Confirmatory factor analysis was used in the pre-test and the final study data to develop and refine measurement instruments, assessing construct validity, identifying method effects and evaluating factor variance across groups. Independent t-tests were used to compare male and female buyers on their evaluation of sales reps.

The results indicate that the gender of the sales person does not seem to be a consideration for male buyers in evaluating reps in any of the variables tested. However, female buyers consistently give less favorable evaluations to female sales people than male sales representatives. The possible implications of these findings are discussed.

First, this research uses a quantitative methodology in both the collection and analysis of the data. Thus, future studies may want to use a qualitative data set to gain a more in-depth understanding of the business-to-business relationships between men and women in the workplace. Also, as the study was concentrated on a relatively small number of business professionals from only one area in China, subsequently researchers should consider increasing the geographic domain where respondents are sampled, to help improve the generalizability of the results.

The gender bias by female buyers found in this study has several important implications for businesses in China. Specifically, the suggests that female buyers may carry with them a “collective negative bias” against other women, in this case, female sales reps. The solution to this problem is not to avoid assigning female sales reps to female buyers, rather, it is to change the negative collective social-esteem identity preconceptions. Organizations can do this through training by making women aware of their own predisposition to unfairly evaluate women that they interact with in the workplace.

It has been argued that gender plays a small role in perceptions of sales representatives in buyer-seller relationships. While this seems to be true in the USA, it has not (until now) been empirically tested in China. Somewhat surprisingly, the gender differences we did uncover are not from male buyers in their assessments, but from female buyers in their evaluation of women sales representatives. This result provides some interesting insight into Chinese business relationships and how some women in positions of power are more critical of other women within their sphere of influence.

The effects of the manipulation of a promised contribution to a university and the personalization of a cover letter on response rate, response speed, and response quality were examined using a commercial population. The results indicate that both the promised contribution to a university and personalization increased response rate and response speed of returns. The influence of the manipulated variables on response quality was mixed. Specifically, only personalization was shown to influence response completeness while neither variable influenced respondents’ willingness to respond to questions that could be regarded assensitive. The study also revealed slight evidence of method‐specific response bias.

The purpose of this paper is to address the following questions: are sophisticated consumers more likely to be satisfied with their purchases? Are consumers who are more knowledgeable more apt to feel in control of their purchase decisions? Are they more likely to believe the transaction was fair? Are they less likely to have cognitive dissonance post‐purchase?

An empirical study examining the role of consumer sophistication on consumers' purchase satisfaction was conducted with a national sample of approximately 700 home purchasers.

The results revealed that shopping sophistication is a key determinant of whether consumers are satisfied with their purchase experience. Sophistication not only seems to affect satisfaction but also customer perceptions of control, fairness and dissonance.

Implications for marketing strategy and suggestions for future research are discussed.

This paper suggests that perception of sophistication plays a much more important role in affecting consumer purchase satisfaction than previously understood. Consequently, businesses need to be much more active in educating consumers so that they are better able to make more informed purchase decisions. Ultimately, by helping to facilitate this information flow, consumers will be more satisfied with the products and services they purchase, develop a greater loyalty to the company providing the data and be more likely to purchase similar products and services in the future.

This study employs creative strategies to contentanalyse Super Bowl commercials from 2001 to 2009, focusing specifically on message strategies. The findings aim to answer four research questions. What are the message strategies commonly employed in Super Bowl commercials? What are the trends of the message strategies employed in Super Bowl commercials over time? What are the relationships between the message strategies and the commercial likeability? What are the specific roles played by the high- vs. low-involvement product categories?

The purpose of this paper is to demonstrate the application of Six Sigma/design of experiments (DOE) hybrid framework for improving damping force (DF) generation process in a shock absorber assembly unit.

The study adopted a case study research method with single case (holistic) design. This research design was found to be appropriate for testing the projected framework for integrating DOE approaches within Six Sigma define-measure-analyze-improve-control (DMAIC) cycle. In the proposed framework, Shainin’s component search technique (CST) was deployed at the “analysis” phase of DMAIC for the first stage filtering of process parameters, followed by the use of Taguchi orthogonal arrays (OA) at the “improve” phase for identifying the optimal setting of the parameters.

The application of Shanin CST facilitated in ascertaining that assembly component (piston with rebound stopper) was causing the variation and not the assembly process. Further, the use of Taguchi OA at the improve phase allowed the collection of necessary data to determine the significant piston parameters with minimum experimentation (eight experimental runs in this case as opposed to the expected 64) and analysis of variance on the collected data facilitated the selection of parameter settings to optimize the “critical to quality”, i.e. rebound DF.

This study provided a stimulus for wider application of integrated DOE approaches by the engineering community in the problem solving and the identification of parameters responsible for poor performance of the process.

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.

Self-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.

The proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.

The choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.

To prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.

To the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

The purpose of this paper is to illustrate the usefulness and results of applying web mining as extensions of data mining.

Web mining is performed using three selected software to databases related to customer survey, marketing campaign data, and web site usage. The three selected software are PolyAnalyst^® of Megaputer Intelligence, Inc., SPSS Clementine^®, and ClickTracks by Web Analytics.

This paper discusses and compares the web mining technologies used by the selected software as applied to text, web, and click stream data.

The limitations include the availability of databases and software to perform the web mining. The implications include that this methodology can be extended to other databases.

The methodology used in this paper could be representative of that used for managers to manage their relationships with customers, their marketing campaigns, and their web site activities.

PolyAnalyst is applied to analyze text data of actual written hotel comments. SPSS Clementine is applied to customer web data collected in response to several different marketing campaigns, including age, gender, and income. ClickTracks is applied to click‐stream data for Bob's Fruit web site to generate click fraud report, search report with revenues, pay‐per‐click, and search keywords for all visitors.

The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First, they are free of functional form assumptions about both utility and weighting functions, and they are entirely based on binary discrete choices and not on matching or valuation tasks, though they depend on assumptions concerning the nature of probabilistic choice under risk. Second, estimated weighting functions contradict widely held priors of an inverse-s shape with fixed point well in the interior of the (0,1) interval: Instead the author usually finds populations dominated by “optimists” who uniformly overweight best outcomes in risky options. The choice pairs used here mostly do not provoke similarity-based simplifications. In a third experiment, the author shows that the presence of choice pairs that provoke similarity-based computational shortcuts does indeed flatten estimated probability weighting functions.

This paper attempts to fill the knowledge gap in the area of foreign direct investment (FDI) research in the regions of Caucasus and Central Asia. Various dimensions of FDI were analyzed from a comparative perspective drawing on a number of selected case studies of inward investors in Georgia and Kyrgyz Republic. The results indicated that the FDI activity in Georgia and Kyrgyz Republic was a market‐seeking type focusing heavily on location‐specific attractions of the two countries. Although the issue of corruption affects foreign investors, it does not act as a major deterrent of FDI infl ows. The most serious problem influencing the performance of FDI firms was found to be inefficiency of local labor force, excessive bureaucracy and red tape, and differences inherent in the business practices of host countries. In general, however, it was found that foreign investors have been satisfied with their performance largely due to the relatively smooth competition and the availability of several market niches in both host country markets.

Digital technologies, and the affordances they provide, can shape institutional processes in significant ways. In the last decade, social media and other digital platforms have redefined civic engagement by enabling new ways of connecting, collaborating, and mobilizing. In this article, we examine how technological affordances can both enable and hinder institutional processes through visibilization – which we define as the enactment of technological features to foreground and give voice to particular perspectives and discourses while silencing others. We study such dynamics by examining #SchauHin, an activist campaign initiated in Germany to shine a spotlight on experiences of daily racism. Our findings show how actors and counter-actors differentially leveraged the technological features of two digital platforms to shape the campaign. Our study has implications for understanding the role of digital technologies in institutional processes as well as the interplay between affordances and visibility in efforts to deinstitutionalize discriminatory practices and institutions.