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The purpose of this paper is to evaluate recent changes made by Australian consumers in their consumption of beef, chicken, pork and lamb, as well as the factors motivating both decreased and increased consumption of each type of meat. Reasons for meat-avoidance are also examined.

An online questionnaire was completed in July 2016 by two Australian samples comprising: adults from the general population; and vegetarians. Data were analysed for 287 meat consumers and 82 meat avoiders. Descriptive statistics and results of multinomial logistic regression models are presented.

Meat consumers most commonly reported reducing consumption of beef in the last 12 months (30 per cent); followed by lamb (22 per cent), pork (14 per cent) and chicken (8 per cent). The following factors were associated with reductions in meat consumption: concerns regarding price and personal health; age and household income; and food choice motivations related to personal benefits, social factors and food production and origin. Main reasons motivating meat-avoidance were concerns regarding animal welfare, health and environmental protection.

This is the first Australian study providing national-level insight on how and why meat consumption patterns are changing. Reasons for changes are examined through an anti-consumption lens, investigating rationale for avoiding, reducing and increasing consumption. This provides a more comprehensive understanding of meat consumption and anti-consumption decisions, which are becoming increasingly complex. Insights on the psychologically distinct motivations underpinning avoidance, reductions and increases in meat consumption can inform the development of strategies aimed at promoting a societal-shift towards consumption of more sustainable dietary protein sources.

To examine the market potential for lab-grown meat (LGM) in Australia by: (1) determining consumers' willingness to consume LGM; (2) exploring heterogeneity in both consumers' willingness to consume LGM and food choice values; and (3) characterizing unique consumer clusters (segments) using socio-demographic, behavioral and psychosocial factors.

Latent class cluster analysis was conducted using online survey data obtained from a nationally representative sample of 1,078 Australian food shoppers.

Six consumer clusters were identified, each distinct in their degree of willingness to consume LGM and in their food choice values. Three clusters (49% of consumers) indicated some willingness to consume LGM. One segment, “Prospective LGM eaters” (12%), appeared “very willing” to consume LGM. These consumers were more likely to be younger (<35 years); university-educated; have greater prior awareness of LGM; stronger beliefs regarding the potential self- and society-related benefits of growing demand for LGM; and higher trust in diverse information sources.

Insights on the characteristics of each cluster provide useful information for the industry on how to tailor product development and marketing strategies to address the needs of consumers with the greatest potential to consume LGM.

This is the first consumer research on the topic of LGM to explore market opportunities for LGM in Australia using a nationally representative consumer sample.

Researchers have been trying to identify different psychological attributes which influence entrepreneurial intention (EI) and role of entrepreneurial education and training programs to develop these attributes among women. Therefore, the purpose of this study is twofold: firstly, to evaluate the difference among psychological attributes before and after an entrepreneurial education and training program. Secondly, to examine the effects of psychological attributes on EI among female students in Saudi Arabia.

A detailed program was designed with the combination of entrepreneurial education and training program throughout a 14-week semester. Data were collected using a structured questionnaire from 310 female university students studying in a Saudi university and participated in this program. SPSS, version 20, was used to analyze the data.

Entrepreneurial education and training programs based on active learning and learner-centered approaches play an important role to significantly improve the level of psychological attributes and EI of female students. Furthermore, findings of this study also suggest that psychological attributes (training retention, self-confidence, tolerance of ambiguity, innovativeness and achievement motivation) positively influence EI.

Previous studies only focused on relationship testing among psychological attributes and EI. This research proposes strategies to design entrepreneurial education and training program to improve psychological attributes and EI which can be considered practical version of EntreComp conceptual model.

Digital transformation becomes the future path for all organizations. Organizations are in need to progress the technology in the event of rapid environmental changes in all aspects. This implies the essential need to adapt to these changes, not only to benefit from the vast opportunities it offers yet even to stay relevant in this instability, complexity, uncertainty and vagueness environment. This paper aims to examine the impact of different variables such as disruptive change, technological process innovation and industry 4.0 (I4.0) on digital transformation. It helps identify the different capabilities needed for digitalization and digital maturity, identify the supporting methods for adopting different technologies and offer answers to overwhelmed those challenges and obstacles resulting in this environment.

A quantitative approach was used in conducting this research, whereas a questionnaire survey strategy was used for this investigation. In total, 450 participants have been surveyed from three major private mining organizations in the Jordanian context. Structural equation modeling was used for the analysis stage and hypotheses testing.

The results of the analysis revealed that support the direct impact of the event of disruptive change, technological process innovation on digital transformation. In addition, the results showed that there is a positive direct impact of the event of disruptive change on technological process innovation. While I4.0 was found to moderate the relationship between the event of disruptive change and digital transformation.

Decision-makers are responsible for directing their organization toward digitalization. This transformation needs capabilities that help organizations in competing and survive in this challenging environment. That is, it is essential to increase process innovation and moving toward more adoption of I4.0. However, the event of disruptive change should be considered as a motivation for the organizations rather than an obstacle. Moreover, different populations, methods and other variables that may affect digitalization may generate novel insights in further research.

Theoretically, novel insights into the event of the disruptive change and its implications have been added to the literature. The models used in the current examination provide new directions for understanding and studying digital transformation and organizational capabilities that are needed for transformation. From the managerial perspective, these findings enhance understanding of practices in which the event of disruptive change supports innovation and highlight the values added through recommending more adopting of I4.0 applications to yield more innovative harvests.

Literature refers to the key factors of total quality management (TQM) based on studies carried out in individual countries. However, few studies focus on studying the TQM factors in service companies based on multinational data. The purpose of this paper is to empirically identify the key TQM factors and their impact on internal and external customer performance measures across different countries.

The research questions regarding the TQM factors and their effects were examined using a sample of service organisations from three countries (131 from Greece, 70 from Mexico and 151 from Spain). TQM factors and their impact on employee and customer satisfaction were analysed separately for each country. Exploratory factor analyses, coupled with multiple linear regression analyses, were conducted.

The key TQM factors identified are common among the three participating countries and can be summarised as follows: quality practices of top management, process management, employee quality management, customer focus, and employee knowledge and education. The adoption level of these five key factors of TQM varies across service organisations in different countries. The results also confirmed that some of the TQM elements are antecedents of customer- and employee-focused performance.

Multinational service organisations may use such an instrument to evaluate TQM implementation among worldwide operations and then benchmark their performance. In addition, an understanding of similarities and differences among countries would help managers around the world to address difficulties of TQM implementation related to the country culture.

Previous studies have compared key TQM factors across different countries in manufacturing, but overall, there has been a little attempt in the literature to analyse the adoption of TQM factors among service firms, as well the relationships between quality improvement and performance across different geographical regions.

Internet of Things (IoT) is an up-and-coming conception that intends to link multiple devices with each other. The aim of this study is to provide a significant analysis of Green IoT. The IoT devices sense, gather and send out significant data from their ambiance. This exchange of huge data among billions of devices demands enormous energy. Green IoT visualizes the concept of minimizing the energy consumption of IoT devices and keeping the environment safe.

This paper attempts to analyze diverse techniques associated with energy-efficient protocols in green IoT pertaining to machine-to-machine (M2M) communication. Here, it reviews 73 research papers and states a significant analysis. Initially, the analysis focuses on different contributions related to green energy constraints, especially energy efficiency, and different hierarchical routing protocols. Moreover, the contributions of different optimization algorithms in different state-of-the-art works are also observed and reviewed. Later the performance measures computed in entire contributions along with the energy constraints are also checked to validate the effectiveness of entire contributions. As the number of contributions to energy-efficient protocols in IoT is low, the research gap will focus on the development of intelligent energy-efficient protocols to build up green IoT.

The analysis was mainly focused on the green energy constraints and the different robust protocols and also gives information on a few powerful optimization algorithms. The parameters considered by the previous research works for improving the performance were also analyzed in this paper to get an idea for future works. Finally, the paper gives some brief description of the research gaps and challenges for future consideration that helps during the development of an energy-efficient green IoT pertaining to M2M communication.

To the best of the authors’ knowledge, this is the first work that reviews 65 research papers and states the significant analysis of green IoT.

The purpose of this paper is to provide a framework for designing a multiple performance measurement tool for evaluating, comparing and benchmarking the working of engineering educational institutes in a group based on total quality management (TQM) criteria and performance measurement criterion, respectively.

Proposed framework is based on fuzzy analytic hierarchy process (FAHP) which takes in to account the fuzziness of human opinion for realistic outcome and generalization of the results. Based on the proposed framework a case study was conducted on engineering institutes of central India for collecting data and analyzing the current practices followed in these institutes. A relationship among TQM implementation criterion was developed, their respective weights derived and then institutes were ranked.

It was found that the rank of institutions based on both the criterion is same, which indicates that the institutes having better TQM implementation have better performance.

The research in this paper is limited to Indian scenario; studies in other countries and sectors may be conducted to compare the results obtained.

The results will help policy makers in identifying institutions having poor performance in the region.

The paper is navel in its attempt to provide a model based on TQM criteria for evaluating the working of engineering educational institutes in a group in terms of their relative weightage and benchmark.