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Prior research on green innovation has shown that institutional pressure stimulates enterprises to adopt green innovation. However, an institutional perspective does not explain why firms that face the same amount of institutional pressure execute different environmental practices and innovations. To address this research gap, the authors linked institutional theory with upper echelons theory and organization performance to build a comprehensive research model.

A total of 800 questionnaires were issued. The final usable questionnaires were 195, yielding a response rate of 24.38%. AMOS 23.0 was used to analyze the data and examine the relationships between the constructs in our model.

Institutional pressures affected both green innovation adoption (GIA) and the top management team's (TMT's) response. TMT's response influenced GIA. GIA was an important factor affecting firm performance. Furthermore, TMT's response mediated the relationship between institutional pressure and GIA. Institutional pressures indirectly affected green innovation performance but did not influence economic performance through GIA. Finally, TMT's response indirectly impacted firm performance through GIA.

The authors draw on institutional theory, upper echelons theory, and a performance-oriented perspective to explore the antecedents and consequences of GIA. This study has interesting implications for leaders and managers looking to implement green innovation and leverage it for firm performance to out compete with market rivals as well as to make the changes in collaboration with many other companies including market rivals to gain success in green innovation.

The majority of institutional investors in Germany use the German income approach (GIA) while investors abroad prefer the discounted cash flow (DCF). The debate around the two methods has been largely theoretical, lacking large-scale empirical evidence. The paper aims to discuss this issue.

The analysis consisted of a performance comparison and hedonic regressions based on ordinary least squares. Fitted GIA and DCF values were obtained for all observations in the data set in order to eliminate distortions caused by different property characteristics in the two valuation sub-samples.

The research hypothesis, stating that the two methods result in statistically identical estimations of value, was rejected. The performance analysis showed that GIA valuations displayed smoother total return performance due to less volatile capital growth in comparison to DCF valuations. Comparing the fitted values obtained from the regressions showed that GIA valuations were on average lower than their DCF counterparts. The difference was small and both methods resulted in very similar fitted values. The difference between fitted values was not constant over time and decreased toward the end of the analysis period.

The research adds empirical arguments to the ongoing debate between GIA and DCF valuations. So far empirical proof has been scarce or one-sided.

This analysis is the first large-scale empirical comparison of the DCF and the GIA within the same market.

International business.

The case is suitable for Bachelor and Master level students of business studies.

In the actual global economy context, firms are trying to be more competitive by accelerating their efforts to integrate foreign markets. Small and medium-sized enterprises (SMEs) from emerging markets are increasingly internationalizing to capitalize on opportunities in foreign markets. To get into internationalization SMEs can use different successful expansion strategies. One of these strategies is the establishment of a win-win partnership with partners that distribute the company products on the foreign markets. The case deals with a successful experience of a win-win partnership from an emerging country SME, the Tunisian food industry firm GIAS, which began its internationalization in 1996. The case presents first the reasons of internationalization of GIAS. Then an explanation of the strategic choices of internationalization of the firm is provided. The selection of the most appropriate foreign markets is described later. The win-win partnership approach is then detailed and the case finishes with the future internationalization plans for GIAS.

The expected learning outcomes include: the selection of a foreign market; the determinants of the foreign mode of entry; the process of integrating an internationalization strategy; how to choose the most appropriate partner; the follow up and the management of the relationships with foreign partners; and the monitoring of international markets. The case provides a space to think about practice and help learners, therefore, to connect theory and practice.

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The purpose of this paper is to construct a key factors selection approach for a class of small-sample multi-factor cross-sectional data analysis (SMCDA) problem, which is very common in productive practice and scientific research, such as coal-bed methane (CBM) content analysis, civil aircraft cost analysis, etc. Key factors selection is an important basic work for SMCDA problem; the proposed method is constructed to improve the accuracy and explanatory of the selected key factors.

Using grey system theory to solve SMCDA problem is more reasonable under few data and poor information. Therefore, this paper constructs a grey incidence analysis (GIA) model with rate of change to select the key factors of an SMCDA problem. The basic idea of the proposed method is to simulate time series by randomly sorting the selected samples, and to calculate the degree of grey incidence with rate of change by loop iterative algorithm, then to construct the degree matrix of grey incidence with rate of change, and finally by which, to utilise quantitative and qualitative analysis methods to select the key factors.

The experimental analysis of application cases demonstrates that the key factors of system’s characteristic can be successfully screened out by the proposed method, the results are consistent with actual conditions, and they have a clearer meaning and a better interpretability.

The method proposed in this paper could be utilised to select key factors for such a class of SMCDA problem, which has fewer observation samples (small-sample), which is influenced by a number of factors (multi-factor) and whose observation samples are placed randomly rather than by time (cross-sectional data). Taking the key influence factors of CBM content and the key driving factors of the vulnerability of agricultural drought in Henan as examples, the results proved the feasibility and superiority of this proposed method.

Most of the existing GIA models mainly focus on these classes of issues with time series data or panel data. However, few GIA models take SMCDA problem as the research object. In this paper, the authors develop the GIA model with rate of change according to the characteristics of SMCDA problem, and present some properties and application suggestions of the proposed method.

A model of the relationships between individuals' perceptions of internet use and internet usage behaviors is presented and tested. The purpose of this paper is to propose that a lack of perceived responsiveness to on‐line communication is positively related to individuals' general resistance to use the internet as a communication information exchange medium, termed general internet apprehensiveness (GIA). Perceptions of GIA are negatively associated with on‐line information‐seeking behavior, and positively associated with individuals' resistance to or fear of using the internet for on‐line retail transactions, termed transactional internet apprehensiveness (TIA).

College‐aged students reported their attitudes about on‐line information seeking, on‐line purchasing, and their on‐line information seeking and purchasing behaviors. The model presented is tested with path analysis to assess the variables' interrelationships.

Ultimately, lack of responsiveness is positively related to GIA, GIA is negatively related to information‐seeking behavior, and TIA is negatively related to consumers' on‐line purchasing of goods and services.

The student sample used in this study prevents us from making broad‐based generalizations. While students represent a large base of internet users and have been presented as a viable population to study in investigations for both academic audiences and marketing practitioners, future research will continue to benefit from more diverse samples of internet users.

This study offers hospitality professionals a better understanding of the elements that inhibit or encourage on‐line information seeking and purchasing behaviors.

This paper further defines the socio‐demographic factors that inhibit consumers from using the internet as both an information‐sharing tool and purchasing medium.

Gender identity assessments (GIAs) have been criticized by practitioners and trans and gender non-conforming (TGNC) individuals alike. With the practice of exploring individuals’ gender identity for treatment pathway purposes being potentially invasive and inappropriate, the current study aims to explore explicit standards.

The current study used the Delphi methodology to survey practitioners familiar with GIA. Over three rounds, 14 international participants rated their agreement about six areas relating to the assessment: purpose; content; approach; forensic application; psychometric instruments; and wider issues. Statements that reached an 80% cut-off among participants were viewed as a sufficient level of agreement, while the remaining items were fed back for repeated ratings. Furthermore, participants had the opportunity to suggest additional items that the group could rate.

Overall, a consensus across 23 items was achieved. The findings indicate a practice emphasizing collaboration between clinician and client to facilitate an informed decision. Furthermore, participants advocated for a non-pathologizing version of the GIA. This is a departure from diagnoses like gender dysphoria toward an approach which encapsulates also positive aspects of the trans experience, for example, resilience and future plans.

Limitations include sampling biases due to participants’ high specialization and challenges in recruiting TGNC individuals. Furthermore, findings appear restricted to adult services.

To the best of the author’s knowledge, this pilot is a first step to making current practice transparent and comparable, with the hopes to improve trans care. Furthermore, it is contextualized with the previously suggested application of the power threat meaning framework to GIA.

This chapter examines discourses and social practices at individual, community, and institutional levels related to non-majority Vietnamese ethnic girls’ access to and participation in secondary school. This critical analysis utilizes Sen's framework of capabilities to illustrate differences in discourse and social practice that exist around poverty, and the ways in which gendered relations and ethnic traditions are intertwined with the discourse and practices of poverty to affect girls’ choices and well-being in and through secondary education. We particularly draw on girls’ and their parents’ constructions of these issues as they negotiate and are affected by them. We argue that strategies must move beyond the discourse that ethnic traditions and gendered relations are barriers to girls’ education to consider the inequalities and lack of capabilities that perpetuate poverty and unequal gendered relations for non-majority ethnic groups in societies.

With the use of the grey incidence analysis (GIA), indicators such as the absolute degree of grey incidence (ε_ij), relative degree of grey incidence (r_ij) or synthetic degree of grey incidence (ρ_ij) are calculated. However, it seems that some assumptions made to calculate them are arguable, which may also have a material impact on the reliability of test results. In this paper, the authors analyse one of the indicators of the GIA, namely the relative degree of grey incidence. The aim of the article was to verify the hypothesis: in determining the relative degree of grey incidence, the method of standardisation of elements in a series significantly affects the test results.

To achieve the purpose of the article, the authors used the numerical simulation method and the logical analysis method (in order to draw conclusions from our tests).

It turned out that the applied method of standardising elements in series when calculating the relative degree of grey incidence significantly affects the test results. Moreover, the manner of standardisation used in the original method (which involves dividing all elements by the first element) is not the best. Much more reliable results are obtained by a standardisation that involves dividing all elements by their arithmetic mean.

Limitations of the conducted evaluation involve in particular the limited scope of inference. This is since the obtained results referred to only one of the indicators classified into the GIA.

In this article, the authors have evaluated the model of GIA in which the relative degree of grey incidence is determined. As a result of the research, the authors have proposed a recommendation regarding a change in the method of standardising variables, which will contribute to obtaining more reliable results in relational tests using the grey system theory.

The rise in malaria deaths discloses a decline of global malaria eradication that shows that control measures and fund distribution have missed its right of way. Therefore, the purpose of this paper is to study and evaluate the impact and control of malaria on the independent states of the Sub-Saharan African (SSA) region over the time period of 2010–2017 using Deng’s Grey incidence analysis, absolute degree GIA and second synthetic degree GIA model.

The purposive data sampling is a secondary data from World Developmental Indicators indicating the incidence of new malaria cases (per 1,000 population at risk) for 45 independent states in SSA. GIA models were applied on array sequences into a single relational grade for ranking to be obtained and analyzed to evaluate trend over a predicted period.

Grey relational analysis classifies West Africa as the highly infectious region of malaria incidence having Burkina Faso, Sierra Leone, Ghana, Benin, Liberia and Gambia suffering severely. Also, results indicate Southern Africa to be the least of all affected in the African belt that includes Eswatini, Namibia, Botswana, South Africa and Mozambique. But, predictions revealed that the infection rate is expected to fall in West Africa, whereas the least vulnerable countries will experience a rise in malaria incidence through to the next ten years. Therefore, this study draws the attention of all stakeholders and interest groups to adopt effective policies to fight malaria.

The study is a pioneer to unravel the most vulnerable countries in the SSA region as far as the incidence of new malaria cases is a concern through the use of second synthetic GIA model. The outcome of the study is substantial to direct research funds to control and eliminate malaria.

In the era of knowledge economy, the significance of intellectual capital has been increasing globally. Similarly, recent studies have focused on the importance of green intellectual capital in mitigating environmental degradation. However, only a few studies have analysed green intellectual capital and its impacts in the specific case of Pakistan. Hence, this study aims to investigate the effects of green intellectual capital on green innovation adoption in Pakistan’s manufacturing small and medium-size enterprises (SMEs).

We used a data sample of 235 SMEs, gathered from the four manufacturing sectors of Pakistan including: textile, chemical, pharmaceutical and steel and analysed using a multiple regression analysis approach.

The empirical results of this research indicate that green human capital and green structural capital significantly increase green innovation adoption. However, it must be noted that green relational capital has a positive but insignificant impact on green innovation adoption in manufacturing SMEs in Pakistan.

The findings and recommended policy measures of this study are important for the managers of manufacturing SMEs and policymakers to mitigate environmental destruction and achieve sustainable development through green intellectual capital.