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Real operational data are used to optimise the performance measurement of air cargo capacity demand management at Virgin Atlantic Cargo by identifying the best KPIs from the range of outcome-based KPIs in current use.

Intelligent fuzzy multi-criteria methods are used to generate a ranking order of key outcome-based performance indicators. More specifically, KPIs used by Virgin Atlantic Cargo are evaluated by experts against various output criteria. Intelligent fuzzy multi-criteria group making decision-making methodology is then applied to produce rankings.

A useful ranking order emerges from the study albeit with the important limitation that the paper looked solely at indices focussing exclusively on outcomes while ignoring behavioural complexity in the production of outcomes.

This paper offers a practical overview of the development of performance measures useful for air cargo capacity demand management.

The aim of this chapter is to understand effects of the recent crisis on the financial constraints that small and medium size enterprises have experienced in emerging economies. Using the firm level survey data provided by the World Bank, a descriptive analysis is conducted by calculating the average of the financial obstacles that the firms had experienced before and after the crisis, and the existence of statistical difference between the two periods is tested. The results indicate that the small and medium size enterprises suffer more from financial constraints relative to large firms. Financial constraints that the small and medium size firms had experienced are largely affected by the recent global financial crisis, relative to the large firms. However, effects of the financial constraints on real variables such as investment, innovation, and research and development expenditures cannot be examined due to data limitations. This chapter contributes to the limited literature of financial constraints experienced by the small and medium enterprises in emerging economies by taking the effect of the recent global financial crisis into account. The novelty of this chapter comes from the dataset: “The World Bank’s World Business Environment Surveys,” which provides a large sample of emerging countries.

The purpose of this paper is to develop and test a theoretical model to examine how exchange climate attributes and contextual factors between two parent firms in an international joint venture (IJV) affect tacit knowledge transfer. The authors investigate how this tacit knowledge, which comprises international marketing expertise, knowledge about foreign cultures and tastes and managerial practices, impacts IJV performance.

Based on data from a survey of IJV managers in 326 Korean firms from a variety of industries, structural equation modeling (AMOS 18.0) is used to test the authors’ hypotheses.

The findings show that conflict resolution and cooperation positively affect tacit knowledge transfer, but communication does not. It was found that the difference in the relative levels of economic development in the environments of partners significantly influences tacit knowledge acquisition, but cultural distance does not. Tacit knowledge acquisition positively influences IJV performance.

The paper fills a gap in the literature by articulating the relationships between exchange climate attributes and tacit knowledge acquisition. Exchange climate, characterized by behavioral processes that directly impact knowledge transfer, constitutes an important missing link in prior research about tacit knowledge transfer. The paper contributes to a better understanding of the dynamic relationships among relational capital, exchange climate and tacit knowledge transfers. The model the authors develop and test has important implications for the design of organizational processes that facilitate tacit knowledge transfer.

Health impact assessment (HIA) is a systematic research and public engagement tool used to elevate health and equity in public policies. However, HIA practitioners often overlook potential mental health impacts. The purpose of this paper is to review the degree to which mental health is included in HIAs in the USA.

The authors conducted a systematic review of 156 HIAs that were completed between 1993 and 2013 for their inclusion of mental health. HIAs were subdivided to assess if mental health conditions or their determinants were measured, and if predictions or mitigation strategies were made in the scoping, assessment, or recommendations phases.

Overall, 73.1 percent of HIAs included mental health. Of the HIAs that included mental health (n=114), 85.1 percent also included the determinants of mental health and 67.6 percent included mental health outcomes. 37.7 percent of HIAs measured baseline mental health conditions and 64.0 percent predicted changes in mental health as the result of implementing the proposed policy, plan, or program. Among the HIAs that made predictions about mental health, 79.5 percent included recommendations for potential changes in mental health, while only 46.6 percent had measured mental health at baseline.

Although many HIAs included mental health in some capacity, this paper quantifies that mental health is not included in a robust way in HIAs in the USA. This presents a difficulty for efforts to address the growing issues of mental health and mental health inequities in the populations.

This paper represents the first academic endeavor to systematically assess the state of the field of HIA for its inclusion of mental health.

Marketers spend considerable resources to motivate people to consume their products and services as a means of goal attainment. Why people change their consumption behaviour is based largely on these goals; many products and services are used by consumers in an effort to attain hoped‐for selves and/or to avoid feared selves. Despite the importance for marketers in understanding how current performance influences a consumer's future efforts, this topic has received little attention in marketing research. The aim of this paper is to fill some of the gaps.

The paper provides a theoretical framework and uses two studies to test this. Study 1, of 203 women, aged 27‐65, examines the predictions in the context of women and visible signs of skin aging. Feedback information is measured and approach and avoidance regulatory systems are manipulated by priming hoped‐for and feared possible selves. Study 2, of 281 undergraduate men and women, replicates the findings of Study 1 with manipulated feedback, using a different context (gym training) and a sample of both male and females.

The research shows that when consumers pursue a hoped‐for self, it is expectations of success that most strongly drive their motivation. It also shows why doing badly when trying to avoid a feared self is more motivating than doing well.

The findings have important implications as they reveal how managers can motivate customers to keep using a product or service.

The paper makes several contributions to the consumer goal research literature since little is known about how positive (hoped‐for selves) and negative (feared selves) reference points in self‐regulation differentially influence consumer goal‐directed behaviour.

This study aims to investigate Malaysian stock market efficiency from the view of Sharīʿah-compliant and conventional stocks based on the effectiveness of technical trading strategies.

This study uses unconventional trading strategies that mix buy recommendations of Bursa Malaysia analysts with sell signals generated from 10 selected technical trading strategies (simple moving average, moving average envelopes, Bollinger Bands, momentum, commodity channel index, relative strength index, stochastic, Williams percentage range, moving average convergence divergence oscillator and shooting star) that are detected using ChartNexus. The period from 1 January 2013 until 31 December 2015 produces a total sample consisting of 1,265 buy recommendations of 125 Sharīʿah-compliant stocks and 400 buy recommendations of conventional stocks. The study period is extended until 31 March 2016 to provide an ample time for detecting the sell signal especially for buy recommendations that are released towards the end of 2015.

The resulting Jensen’s alpha show 8 out of 10 strategies are effective in generating abnormal returns in Sharīʿah-compliant samples while only 3 out of 10 strategies are effective in conventional samples. Prominent effectiveness of technical trading strategies in Sharīʿah-compliant stocks implies clear inefficiency in that stock market segment as opposed to those of the conventional stocks.

The results based on unconventional trading strategies provide new insights of Malaysian stock market efficiency especially in Sharīʿah-compliant and conventional stocks. The paper provides more robust findings on market efficiency as firms’ equity level data were focussed together with analysts’ buy recommendations from Bursa Malaysia.

Virtual teams had become a fundamental way to conduct business for organizations to remain competitive and sustain in a global environment. Organizations which willing to understand what makes virtual teams more effective can likely accrue positive results from virtual teams. Hence, the purpose of this paper is to investigate what are the factors that impact the performance of virtual team. This study highlights factors that influence virtual team performance, which not been widely studied in developing countries (i.e. Malaysia). This study tests the impact of six factors (coordination, communication, relationship building, cohesion, trust and reward) on team performance.

A quantitative approach via self-administered questionnaire was adopted. A total of 205 questionnaires were successfully collected at the end of the data collection. Structural equation modelling using partial least squares approach (i.e. ADANCO 2.0 software) was then used to assess the relationships among variables in the virtual team.

After ensuring the data have acceptable reliability and validity, structural model assessment was performed to test the hypotheses. The results indicated that a significant and positive relationship exists between communication, relationship building, cohesion and trust towards team performance. On the other hand, no significant relationship was found between coordination and reward towards team performance.

First, the study may be slightly biased due to the differences in the size of the multinational companies. The result might tend to represent the bigger companies where more virtual teams are available for sampling of this study. Second, the duration of virtual team (long-term and short-term) and the number of sites in the team should be clearly identified. The respondents might have very different experiences and perceptions in different settings of virtual team environment. Therefore, taking care of these characteristics would have provided a more detailed and comprehensive understanding of factors influencing virtual team performance in Malaysia.

The findings from this study can serve as guideline for managers to manage the virtual teams effectively, as well as to optimizes the resources usage and implement the most efficient tools of communication, and subsequently improve the overall efficiency of the teams. This study is useful for researchers, managers and organizations to highlight the factors that contribute to virtual team performance.

The present study has not only extended the use of Media Richness Theory in the context Virtual Team Performance in a developing country but also broadened the previous study through inclusion of other crucial factor, namely, Reward. Given the significant role in the Global marketplace, the understanding of factors influencing virtual team performance in Malaysia using the extended theory of Media Richness would contribute knowledge not only to technology management but also to manufacturing service industry.

The purpose of this study is to highlight key issues pertaining to making use of Islamic equity indices and proposing possible solutions to address the problems faced in advancement of the concept of Shariah investing (SI) with the aim to advance the discourse on the subject.

Online focus group discussion (FGD) was carried out in which ten Islamic finance researchers and analysts belonging to institutions considered as authority on the subject matter participated to share their viewpoints on Islamic equity indices. Content analysis on the collected data of FGD was carried out which has revealed six key themes.

Six broader themes were identified based on the analysis of FGD, which includes criteria for constructing Islamic equity indices, utilization of Islamic equity indices for comparison with conventional stock indices, stock market efficiency perspectives, reason for integration of different equity markets, investors’ awareness of SI and future directions of Islamic equity indices. Results of the study indicate that Islamic finance researchers and analysts opined that there is a need for revising the criteria for construction of Islamic equity indices. There are conflicting viewpoints regarding performance and efficiency of Islamic indices in comparison with conventional indices and main reasons for stock market integration are trade liberalization, globalization and other factors. Moreover, there is a need for making investors and other market players aware about the attractiveness of Islamic indices from investing point of view.

Based on this extensive literature review and as highlighted by Masih et al. (2018) in their recap of literature on Islamic equity indices indicating that there are bulk of empirical studies carried in the past in the domain, however, there is a dearth of theoretical and qualitative studies. Hence, this preliminary qualitative study not only makes theoretical contribution but also deploys FGD, which is rarely used in the similar context, and offers candid views of the participants on key issues pertaining to Islamic equity indices. This lends novelty to this study.

To overcome the shortcomings of traditional industry classification systems such as the Standard Industrial Classification Standard Industrial Classification, North American Industry Classification System North American Industry Classification System, and Global Industry Classification Standard Global Industry Classification Standard, the authors explore industry classifications using machine learning methods as an application of interpretable artificial intelligence (AI).

The authors propose a text-based industry classification combined with a machine learning technique by extracting distinguishable features from business descriptions in financial reports. The proposed method can reduce the dimensions of word vectors to avoid the curse of dimensionality when measuring the similarities of firms.

Using the proposed method, the sample firms form clusters of distinctive industries, thus overcoming the limitations of existing classifications. The method also clarifies industry boundaries based on lower-dimensional information. The graphical closeness between industries can reflect the industry-level relationship as well as the closeness between individual firms.

The authors’ work contributes to the industry classification literature by empirically investigating the effectiveness of machine learning methods. The text mining method resolves issues concerning the timeliness of traditional industry classifications by capturing new information in annual reports. In addition, the authors’ approach can solve the computing concerns of high dimensionality.

Considers the implications of EMU and the introduction of the euro for European financial institutions and markets. Discusses the likely effects on interest rates, banks, stock/futures exchanges, asset allocation and the markets for bonds, equities and derivatives. Warns that financial markets and institutions must adjust to these changes in order to survive, but believes that European economies will benefit in the long run.