Understanding consumer participation in managing ICT waste: Findings from two-staged Structural Equation Modeling-Artificial Neural Network approach

Temporal-spatial assessment of the vulnerability of human settlements in urban agglomerations in China

Although many studies have focused on the livability and satisfaction of the human settlement environment in Chinese cities, few have paid attention to the vulnerability of human settlements in urban agglomerations in China (VHSUAC). The analytic hierarchy process and the entropy method are combined in this paper to comprehensively weight the constructed four-dimensional evaluation index system. Then, we identified the key factors influencing VHSUAC. Finally, we use the environmental vulnerability index (EVI) to calculate the vulnerability value from 2008 to 2017 and display the vulnerability changes over time and space using ArcGIS software. The results show that (1) from the perspective of temporal pattern, VHSUAC showed a downward trend from 2008 to 2017, but the degree of decline in each urban agglomeration was not equal. There is a certain difference in the vulnerability value of the human settlement environment between the urban agglomeration and its inner cities, and their direction of change is not always the same. (2) From the perspective of spatial pattern, VHSUAC has obvious regional heterogeneity, presenting a spatial pattern of "low coastal areas and high inland areas." Coastal urban agglomerations pay more attention to the optimization of the human settlement environment. (3) In terms of influencing factors, the vulnerability values of the four system indicators are listed in the following order: economic support environment>urban ecological environment>public service environment>urban living environment. We found that domestic waste and sewage treatment have a more obvious impact on VHSUAC.

What Influences Home Gardeners’ Food Waste Composting Intention in High-Rise Buildings in Dhaka Megacity, Bangladesh? An Integrated Model of TPB and DMP

Composting is a sustainable way of transforming organic waste into valuable organic fertilizers which have the potential to act as soil conditioners by controlling various biological processes. The prime objective of the current study was to determine the influencing factors behind the intent of home food waste composting, by employing the combined model of Theory of Planned Behavior (TPB) and Dualistic Passion Model (DMP). The combined model showed a higher predictive ability in comparison to the individual TPB model. The fit statistic of the integrated model was deemed good, and 65% of the variance for home composting intention was explained. Using a face-to-face questionnaire survey, a total of 203 valid responses were gathered from home gardeners and tested via a unique two-step methodology: the PLS-SEM and the artificial neural network (ANN). The results revealed that the composting intention can be significantly influenced by attitude, subjective norms, and perceived behavioral control. The study also confirmed the positive effect of harmonious passion and the negative effect of obsessive passion on the intention of food waste composting. Furthermore, the hybrid method produced more reliable results because HP was found to be the most important variable in both ANN and PLS-SEM results, while PBC was observed to be the second most important variable in ANN and the fourth most important in PLS-SEM. The results of the current study not only highlight the importance of passion in determining food waste composting intention in Dhaka, Bangladesh, but also provide helpful information for designing effective, sustainable tactics for encouraging residents to compost food waste at home.

Consumer behaviour towards storage, disposal and recycling of e-waste: systematic review and future research prospects

Purpose

With the rapid increase in the consumption of electrical and electronic innovations, responsible management and recycling of electronic waste (e-waste) or waste electrical and electronic equipment (WEEE) has been a significant concern for the governments, stakeholders, researchers and industry practitioners around the world. Consumer awareness, disposal behaviour and perception are chief facets of designing sustainable management strategies. Although researchers have widely studied e-waste over many years, the research focusing on consumer awareness about e-waste recycling has gained momentum recently. This paper aims to systematise the existing literature and explore future research prospects on household e-waste sorting behaviour.

Design/methodology/approach

Web of science (WoS) core collection was searched using selected keywords to identify relevant articles published from 2001 to 2021. The search resulted in 1,156 research articles published from 2001 to 2021. After a detailed study, 85 articles were shortlisted for in-depth review. The review was conducted based on global trends, top journals, most prolific authors, most active e-waste research countries, and institutions centring on consumer participation in e-waste disposal and recycling behaviour. The present research has also identified around eleven factors that seem to have a bearing on consumer behaviour towards storage, disposal and recycling of e-waste.

Findings

E-waste research has gained increased attention in the last five years. The majority of the studies has focused on motivational factors and ignore the risks associated with handling e-waste. The present study reports the pertinent issue of lack of awareness among the masses about e-waste handling and disposal. Thus, bringing to the fore the lack of awareness programmes and initiatives. The analysis presents the gaps in the literature and future research agendas.

Originality/value

The review article will help in providing an in-depth understanding of consumer behaviour towards storage, disposal and recycling of e-waste and delineates the future direction of research that may be undertaken in this field of study.

Hybrid artificial neural network and structural equation modelling techniques: a survey

Topical treatments with structural equation modelling (SEM) and an artificial neural network (ANN), including a wide range of concepts, benefits, challenges and anxieties, have emerged in various fields and are becoming increasingly important. Although SEM can determine relationships amongst unobserved constructs (i.e. independent, mediator, moderator, control and dependent variables), it is insufficient for providing non-compensatory relationships amongst constructs. In contrast with previous studies, a newly proposed methodology that involves a dual-stage analysis of SEM and ANN was performed to provide linear and non-compensatory relationships amongst constructs. Consequently, numerous distinct types of studies in diverse sectors have conducted hybrid SEM-ANN analysis. Accordingly, the current work supplements the academic literature with a systematic review that includes all major SEM-ANN techniques used in 11 industries published in the past 6 years. This study presents a state-of-the-art SEM-ANN classification taxonomy based on industries and compares the effort in various domains to that classification. To achieve this objective, we examined the Web of Science, ScienceDirect, Scopus and IEEE Xplore ^® databases to retrieve 239 articles from 2016 to 2021. The obtained articles were filtered on the basis of inclusion criteria, and 60 studies were selected and classified under 11 categories. This multi-field systematic study uncovered new research possibilities, motivations, challenges, limitations and recommendations that must be addressed for the synergistic integration of multidisciplinary studies. It contributed two points of potential future work resulting from the developed taxonomy. First, the importance of the determinants of play, musical and art therapy adoption amongst autistic children within the healthcare sector is the most important consideration for future investigations. In this context, the second potential future work can use SEM-ANN to determine the barriers to adopting sensing-enhanced therapy amongst autistic children to satisfy the recommendations provided by the healthcare sector. The analysis indicates that the manufacturing and technology sectors have conducted the most number of investigations, whereas the construction and small- and medium-sized enterprise sectors have conducted the least. This study will provide a helpful reference to academics and practitioners by providing guidance and insightful knowledge for future studies.

A framework for measuring customer loyalty for 3PL industry: a case of evolving market

Purpose

This research aims to propose a framework for measuring customer loyalty for third party logistics (3PL) industry by exploring the attributes that are more attractive to customers and ascertain the mechanisms for increasing customer loyalty in 3PL industry.

Design/methodology/approach

Data were collected from one hundred and thirty-three (133) respondents who were employees of different industries that outsource 3PL services. The partial least square structural equation modeling (PLS–SEM) was deployed for analysis.

Findings

The results showed that service quality has a significant positive impact on customer orientation, customer satisfaction and relationship quality. On the other hand, customer orientation has been observed to positively impact customer satisfaction but an insignificant impact on customer loyalty and relationship quality. Customer satisfaction has a significant positive impact on relationship quality but an insignificant impact on customer loyalty. Also, relationship quality has a significant positive impact on customer loyalty.

Practical implications

The results recommend that 3PL companies' managers focus more on developing quality relationships with their customers, delivering exemplary service quality and offering customer orientation.

Originality/value

This study will help the stakeholders gain much more understanding and insights on how competitive advantage can be achieved and, consequently, help 3PL become the market leaders.