Modelling Organisational Factors Influencing Sustainable Development Implementation Performance in Higher Education Institutions: An Interpretative Structural Modelling (ISM) Approach

open access articleGlobally, higher education institutions (HEIs) have continued to record varied sustainable development (SD) implementation performances. This variance has been attributed to the presence of certain organisational factors. Whereas previous studies have successfully identified the factors influencing the SD implementation performance in HEIs, few studies have attempted to explore the relationship between these factors and the influence of such a relationship on the management of SD implementation in HEIs. This is the objective of this study. Understandably, an understanding of such relationships will facilitate the development of appropriate frameworks for managing SD implementation in HEIs. Relying on a case study of a South African University of Technology (SAUoT), this study elicits data through a focus group discussion session. An interpretative structural modelling (ISM) focus group protocol indicating extant pair-wise relationships between identified organisational factor categories was extensively discussed. The emergent data was recorded, transcribed verbatim and subsequently analysed. The findings suggest that communication was critical to the prevalence of other factors, hence indicating its centrality to the effective management of SD implementation in HEIs. These findings will guide implementing agents in HEIs towards developing appropriate strategies for communicating SD implementation strategies

Knowledge management in sustainable supply chain management: improving performance through an interpretive structural modelling approach

Sustainable supply chain management is one vital element in achieving competitive advantage in business management and knowledge management is seen to be one key enabler. However, in previous studies the interrelationships between knowledge management and sustainable supply chain management are still under-explored. This study proposes a set of measures and interpretive structural modelling methods to identify the driving and dependence powers in sustainable supply chain management within the context of knowledge management, so as to improve the performance of firms from the textile industry in Vietnam. The research result indicated that learning organisation, information/knowledge sharing, joint knowledge creation, information technology and knowledge storage are amongst the highest driving and dependence powers. These attributes are deemed to be most-effective to enhance the performance of firms. To further enhance the value of this research, theoretical and managerial implications are also discussed in this study

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

Analyzing Students’ Technology Use Motivations: An Interpretive Structural Modeling Approach

Despite being more meaningful and accurate to consider student technology use motivations as a set of interactive needs and expectations, the possible underlying hierarchical relationships among motivations receive little attention. Drawn from Uses and Gratifications (U&G) approach and from Means-End Chain (MEC) theory, this study investigates how student technology use motivations can be represented as a set of interrelated and hierarchically organized elements. A set of relevant data concerning students’ technology use motivations was collected by the Repertory Grid Interview Technique (RGT) and analyzed qualitatively using content analysis. Eleven identified student technology use motivations were structured by adopting interpretive structure modeling (ISM) technique. By using Multiplication Applied to Classification (MICMAC) technique, eleven identified factors were further classified into three different types of variables: means, consequences, and ends. The findings of this study have significant theoretical and practical implications to both researchers and managers

Identification and Modelling of Religious Tourism Supply Chain Enablers in Post-Covid Era Using ISM

Post-Covid-19 pandemic, the supply chains of all the trades faced a setback, but the tourism sector faced an extended jolt of this disaster. Religious tourism, which has been adding a sizeable revenue to Indian GDP, came to a downfall. This manuscript aims to identify and model the enablers of the religious tourism supply chain for reviving the economy in the post-Covid era. The research paper elucidates that post-shock of Covid-19, understanding religious tourism enablers will provide opportunities to all the stakeholders of this chain. Eleven enablers for the religious tourism supply chain were identified. The modelling of these enablers using ISM (Interpretive Structural Modelling), provides insight into their hierarchy and interdependence upon each other. The ISM model also illustrates that the enabler Pilgrims belief and value, a mandatory obligation is the most crucial enabler and influence all other enablers. Religious tourism supply chain stakeholders can employ this model to formulate strategies to overcome the post-pandemic challenges. Subsequently focusing upon the key enablers essential in reviving the tourism sector economy.

Drivers of Success to Effective Entrepreneurship: A Comparison of Immigrant and Native-born Perceptions

The literature indicates that only a few studies have compared immigrant and non-immigrant entrepreneurs in the United States. The present study addresses this gap by inquiring how these populations perceive drivers of success. I employed an in-depth, multi-case analysis of immigrant and nonimmigrant entrepreneurs operating in the United States. Data were collected from semi-structured interviews. Adaptive comparative causal maps (CCMs), which are qualitative methodological tools, were used to illustrate similarities and differences between the groups. I identified 155 drivers of success. I ascertained connections, deviations, and causal linkages as well as portrayed overlaps and divergences in the groups’ perspectives regarding the perceptions of success drivers. There were many differences detected between the groups, such as immigrants’ views that being innovative and able to adapt to trends (entrepreneurial orientation (EO)), being dynamic (EO), and able to build a reliable team (business orientation (BO)) influence success. Nonimmigrants perceived that communicating with customers (BO) and the ability to calculate risks (EO) are the factors that affect success. Despite having many differences, both groups regarded BO drivers (e.g., leadership skills, market orientation, and financial capabilities) as the most influential determinants of success. Among EO drivers, the groups indicated that innovative capability exerts the most significant effect on success. This study contributes to research and practice through its determination of immigrant and nonimmigrant perceptions of EO and BO drivers and their effects on entrepreneurial success. The findings are expected to assist practitioners, scholars, and educators in formulating improved strategies and creating training programs for developing EO and BO factors and, consequently, clear the way for entrepreneurial success. This is the first qualitative study that utilized the research model that incorporated both EO and BO to observe the separate effects of these orientations on entrepreneurial success, the first study that compares immigrant and nonimmigrant perceptions of drivers of success, and the first in the business and entrepreneurship disciplines to employ and build on the CCM technique. Overall, the research adds to the existing body of knowledge by filling the gap in how the aforementioned method is used, wherein rules and regulations for standard dimensional gauges are lacking