Search results

The purpose of this special issue is to extend the growing research on the challenges and opportunities facing services marketers in an increasingly culturally diverse global marketplace.

The nine papers included in this special issue use a variety of research methods (e.g. case study, experiments and surveys), participants (e.g. customers, employees and online panel members) and service settings (e.g. fast food, post office, weight loss, bank, home loan, personal fitness and offshore outsourcing).

All the nine papers highlight the importance of studying the unique perspectives of the customers and employees involved in intercultural interactions in diverse service settings in marketplaces and societies that are either already or have recently become multicultural.

The findings from the nine papers have useful implications for future research on services marketing in multicultural markets, although these may not always be generalisable beyond the unique context of the studies reported in each of these papers.

All the nine papers also present some useful directions for services marketing managers in the multicultural markets, to help them understand and manage the expectations of their culturally diverse customers, as well as employees.

This special issue is unique because it is one of the first attempts to understand the unique challenges and opportunities for services marketers in the growing multicultural global marketplace, from a theoretical, as well as empirical, point of view.

The purpose of this paper is to address a long-standing gap in current research on intercultural service encounters, by exploring the direct and indirect roles of four personal cultural orientations (PCOs) [independence, interdependence (INT), risk aversion (RSK) and ambiguity intolerance (AMB)].

A 2 × 2 between-subjects experimental design with customers in two countries (Australia and China) using scenarios to manipulate service outcome (failure or success) and photos of foreigners as customer or employee to prime perceived cultural distance (PCD).

Customers with higher (vs lower) independence perceive greater interaction comfort, service quality and satisfaction (SAT) and are affected to a lesser extent by PCD and service outcome, but those with higher (vs lower) RSK or AMB perceive lower interaction comfort, service quality and SAT and are affected more strongly by PCD and service outcome.

The authors used an “experimental” design with “imaginary” service scenarios to collect data in “two” countries using “four” PCOs for greater control in this paper, but all of these choices may restrict the generalizability of the findings.

Service managers need to look beyond visible cultural differences, such as ethnicity, nationality and language, and focus more on the invisible cultural differences in customs, values and norms, as reflected by the four PCOs in this paper.

The authors extend prior research on intercultural service encounters by exploring the moderating effects of PCOs on the influence of service outcome and PCD on interaction comfort, service quality and SAT.

The purpose of this paper is to introduce a new conceptual model that incorporates internal service quality as a mediator between service climate and employee performance and two personal cultural orientations (independence and interdependence) as the moderators of these relationships.

An online survey of 353 employees representing 19 different nationalities, working in 18 branches and offices of a multinational business-to-business (B2B) civil engineering services firm, spread across 14 countries.

All the hypotheses are supported. Specifically, internal service quality mediates the influence of service climate on employee performance and these relationships are stronger for employees with interdependent (vs independent) cultural orientations.

This paper uses data collected from the employees in a single B2B firm in one industry (Civil Engineering Services) and focuses on a few key variables, which may restrict the generalizability of its findings.

The findings of this paper highlight the importance of cultural factors in building a service climate in multinational service organizations to help their employees work more effectively and efficiently with their colleagues from diverse cultural backgrounds.

This paper clarifies the relationships among service climate, internal service quality and employee performance, by showing that internal service quality mediates the influence of service climate on employee performance.

The purpose of this paper is to establish the effect of top management team (TMT) cultural diversity on firm performance with a framework that considers such an effect from both cost and benefit perspectives. The paper also examines whether and how diversity management mechanisms such as socialisation and tenure may moderate the effect of TMT diversity on firm performance.

Drawing upon two competing perspectives of resource-based view (RBV) and transaction cost economics (TCE), this paper theorises and tests the potential positive and negative effects of TMT cultural diversity on firm performance with 442 publicly listed IT companies in the USA.

The results supported the RBV prediction that TMT cultural diversity enhances firm performance and socialisation strengthens the positive effects of a culturally diverse TMT on firm performance. However, tenure was not found to be important in promoting diversity gains or mitigating diversity costs. By showing clear support for the RBV prediction of the positive impact of TMT cultural diversity and refuting the TCE prediction of the potentially negative effects, this research strengthens the business case for embracing cultural diversity in TMTs.

This paper contributes to the current literature by developing a more balanced framework to deepen our knowledge of how TMT cultural diversity may impact firm performance, and how the use of socialisation and tenure may moderate the TMT cultural diversity–firm performance relationship from both cost and benefit perspectives.

This paper aims to investigate the individual difference on digital reading, by examining the eye-tracking records of male and female readers with different reading ability (including their pupil size, blink rate, fixation rate, fixation duration, saccade rate, saccade duration, saccade amplitude and regression rate).

A total of 74 participants were selected according to 6,520 undergraduate students’ university entrance exam scores and the follow-up reading assessments. Half of them are men and half are women, with the top 3% good readers and the bottom 3% poor readers, from different disciplines.

Results indicated that the major gender differences on reading abilities were indicated by saccade duration, regression rate and blink rate. The major effects on reading ability have a larger effect size than the major effect on gender. Among all the indicators that have been examined, blink rate and regression rates are the most sensitive to the gender attribute, while the fixation rate and saccade amplitude showed the least sensitiveness.

This finding could be helpful for user modeling with eye-tracking data in intelligent tutoring systems, where necessary adjustments might be needed according to users’ individual differences. In this way, instructors could be able to provide purposeful guidance according to what the learners had seen and personalized the experience of digital reading.

This paper aims to first apply more advanced anisotropic yield criterions as Yld91 and Yld2004 to spherical indentation simulations, and investigate plastic anisotropy identified from indentation simulations following different yield criterions (Hill48, Yld91, Yld2004) to discover laws. It also aims to compare the difference in plastic anisotropy identified from indentation on three yield criterions and evaluate the applicability of plastic anisotropy.

This paper uses indentation simulations on different yield criterions to identify plastic anisotropy. First, the trust-region techniques based on the nonlinear least-squares method are used to determine anisotropy coefficients of Yld91 and Yld2004. Then, Yld91 and Yld2004 are implemented into ABAQUS software using user-defined material (UMAT) subroutines with the proposed universal structure. Finally, through considering comprehensively the key factors, the locations of the optimal data acquisition points in indentation simulations on different yield criterions are determined. And, the identified stress–strain curves are compared with experimental data.

This paper discovers that indentation on Yld2004 is able to fully identify difference in equivalent plastic strain between 0° and 90° directions when indentation depth h_t is relatively smaller. And, this research demonstrates conclusively that plastic anisotropy identified from indentation on Yld2004 and Yld91 is more applicable at larger strains than that on Hill48, and that on Yld2004 is more applicable than that on Yld91, overall. In addition, the method on the determination of the locations of the optimal data acquisition points is demonstrated to be also valid for anisotropic material.

This paper first investigates plastic anisotropic properties and laws identified from indentation simulations following more advanced anisotropic yield criterions and provides reference for later research.

A mathematical model and numerical method for water flow and solute transport in a tidal river network is presented. The tidal river network is defined as a system of open channels or rivers with junctions and cross sections. As an example, the Pearl River in China is represented by a network of 104 channels, 62 nodes, and a total of 330 cross sections with 11 boundary sections for one of the applications. The simulations are performed with a supercomputer for seven scenarios of water flow and/or solute transport in the Pearl River, China, with different hydrological and weather conditions. Comparisons with available data are shown. The intention of this study is to summarize previous works and to provide a useful tool for water environmental management in a tidal river network, particularly for the Pearl River, China.

For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their aggregation. Performance prediction for ranking aggregation can solve this issue effectively. However, the performance prediction effect for ranking aggregation varies greatly due to the different influencing factors selected. Although questions on why and how data fusion methods perform well have been thoroughly discussed in the past, there is a lack of insight about how to select influencing factors to predict the performance and how much can be improved of.

In this paper, performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task is studied. An influencing factor optimization selection method based on stepwise regression (IFOS-SR) is proposed to screen the optimal influencing factors. A working group selection model based on the optimal influencing factors is built to select the optimal working group with a given number of workers.

The proposed approach can identify the optimal influencing factors of ranking aggregation, predict the aggregation performance more accurately than the state-of-the-art methods and select the optimal working group with a given number of workers.

To find out under which condition data fusion method may lead to performance improvement for ranking aggregation in crowdsourcing task, the optimal influencing factors are identified by the IFOS-SR method. This paper presents an analysis of the behavior of the linear combination method and the CombSUM method based on the optimal influencing factors, and optimizes the task assignment with a given number of workers by the optimal working group selection method.

Drawing on the resource‐based view and organizational learning theory, this study aims to examine the effect of resources and capabilities on international joint venture (IJV) performance.

Departing from the extant research which largely assumes a bipartite relationship, the present study views an IJV as representing a tripartite relationship involving the IJV, its foreign parent and its local parent. Accordingly, it examines the effect of resources contributed by both foreign and local parents on IJV performance. It also examines how the IJV's absorptive capacity moderates the relationship between resource acquisition and performance.

Results from a survey of 102 IJVs in China provide general support for the argument that performance of IJVs seems to be driven by the complementary resources of partner firms in combination with absorptive capacity of IJV.

The findings from this study are useful for researchers interested in performance of iIJVs.

The quick growth of web-based and mobile e-learning applications such as massive open online courses have created a large volume of online learning resources. Confronting such a large amount of learning data, it is important to develop effective clustering approaches for user group modeling and intelligent tutoring. The paper aims to discuss these issues.

In this paper, a minimum spanning tree based approach is proposed for clustering of online learning resources. The novel clustering approach has two main stages, namely, elimination stage and construction stage. During the elimination stage, the Euclidean distance is adopted as a metrics formula to measure density of learning resources. Resources with quite low densities are identified as outliers and therefore removed. During the construction stage, a minimum spanning tree is built by initializing the centroids according to the degree of freedom of the resources. Online learning resources are subsequently partitioned into clusters by exploiting the structure of minimum spanning tree.

Conventional clustering algorithms have a number of shortcomings such that they cannot handle online learning resources effectively. On the one hand, extant partitional clustering methods use a randomly assigned centroid for each cluster, which usually cause the problem of ineffective clustering results. On the other hand, classical density-based clustering methods are very computationally expensive and time-consuming. Experimental results indicate that the algorithm proposed outperforms the traditional clustering algorithms for online learning resources.

The effectiveness of the proposed algorithms has been validated by using several data sets. Moreover, the proposed clustering algorithm has great potential in e-learning applications. It has been demonstrated how the novel technique can be integrated in various e-learning systems. For example, the clustering technique can classify learners into groups so that homogeneous grouping can improve the effectiveness of learning. Moreover, clustering of online learning resources is valuable to decision making in terms of tutorial strategies and instructional design for intelligent tutoring. Lastly, a number of directions for future research have been identified in the study.