Resilience is one of the constructs which received less attention in the contemporary entrepreneurial literature. This paper explored the relationships among social capital, commitment and career resilience of entrepreneurs in Northern Nigeria. 576 active entrepreneurs were selected to participate in this study using cluster sampling approach and were served with questionnaires of which 390, representing 68% response, were retrieved. The data were analyzed using Smart-PLS 3 software of Partial Lease Square Structural Equation Modelling (PLS-SEM). The findings suggest that bonding social capital influenced both career commitment as well as career resilience, but bridging did not. In addition, career commitment mediated the relationship between bonding social capital and career resilience, but did not mediate the relationship between bridging social capital and career resilience. Theoretical, practical and methodological implications were also provided.

Consumers’ consumption culture of the twentieth century has culminated into environmental degra-dation and its adverse consequences on health and the ecosystem. Despite these concerns, consumers still fail to purchase environmentally-friendly or green products due to the lack of awareness and belief about the benefits of such products. This study seeks to understand consumers’ attitude towards green products by investigating the effect of consumers’ green product knowledge, green product belief, environment affect and environmental concern on green product purchase intention drawing on the cognitive-affect-behaviour model. Multiple regression analysis was used to analyse the data from 348 Health workers from a South-eastern Health Institution in Nigeria and examined the proposed hypotheses. The result shows that green product purchase intention was significantly influenced by green product knowledge and environmental affect but no significant effect was found for green product belief and environmental concern. Environmental effects had the most im-pact on green product purchase intention. Therefore, it is recommended that marketers focus their marketing campaigns towards educating consumers on the availability and benefits of green prod-ucts by using eco-labels and emphasizing the health and environment benefits of green products; appealing to consumers’ morals and emotions in marketing campaigns for green products to spur consumers’ interest in green products and adopting a green lifestyle.

The recent paradigm shift from recruitment of international students to retention of students encouraged radical changes on the consumption of educational services from university serving the students for creation of mutually beneficial relationship between the students and the university. The impact of globalization hit the economy in two paradoxes; first, consumers have more choices but less satisfaction; second, service providers have more strategic options, which yield less value. Against this background, this study proposed and validated destination loyalty model to arrest the increasing students’ attrition at study location. The declining state funding of higher education challenged the management of education sector to design sustainable competitive advantage strategy not only to attract but also to retain students at their study destination. A total of 498 data was solicited from international students at Malaysian public universities, partial least square structural equation modeling (PLS-SEM) was used to test the reliability and validity of items and constructs. The results show that relationship marketing dynamism of service quality, students’ satisfaction, perceive image, perceived value and personal reasons were stable for international student loyalty to study destination. A new model called 2S2P was developed for emerging education destinations. Theoretical and practical implications as well as directions for future studies were documented in the paper.

The growing convolution of industries and the need for corporate business survival has created a cognizance dilemma on the nexus of earnings management and managerial compensation paradigm, especially in developing nations. Hence, this paper sought to examine the nexus of earnings management and managerial compensation in Nigerian manufacturing firms. The study collected panel data from audited annual financial reports of six selected manufacturing firms listed in the Nigeria Stock Exchange, covering the period from, 2012-2019. The data were analyzed using descriptive statistics, correlation and Panel Regression Model. The findings indicate that earnings management is a significant determinant of managerial remuneration. Therefore, the study concludes that managing earnings of firms has a positive significant relationship with executive remuneration, and as such compensation should be tied to performance of the firm in real values.

The classification of large-scale textual dataset is associated with a huge number of instances and millions of features which must be discriminated between large numbers of categories. The task requires the utilization of a defined hierarchy structure and tools that automatically classify instances within the hierarchy known as Large Scale Hierarchical Text Classification (LSHTC). Predicting the labels of instances by the employed classifiers is challenging due to the high number of features. Furthermore, the existing Dimensional Reduction (DR) approaches in cooperation with the LSHTC framework are still quite inefficient. In such a problem, an effective Hierarchical Dimensional Reduction approach can be advantageous in improving the performance of the LSHTC. Therefore, in this paper, we enhance the performance of LSHTC by proposing a Multi-stage Hierarchical Dimensional Reduction (MHDR) approach based on Modified Feature Hashing (MFH) and Hierarchical Bi-Filtering (HBF) method. In addition to alleviating bad collision and result discrepancy, experimental results show that the proposed approach has achieve the best performance in terms of micro-f1 and macro-f1 by recording average scores of 58.47% and 54.77% using TD-SVM, and average scores of 51.14% and 48.70% using TD-LR, respectively. The method also achieved 11% speed-up than the approaches compared.

This paper presents a new penalty function called logarithmic penalty function (LPF) and examines the convergence of the proposed LPF method. Furthermore, the LaGrange multiplier for equality constrained optimization is derived based on the first-order necessary condition. The proposed LPF belongs to both categories: a classical penalty function and an exact penalty function, depending on the choice of penalty parameter. Moreover, the proposed LPF is capable of dealing with some of the problems with irregular features from Hock-Schittkowski collections of test problems.

This paper proposes a framework for selecting energy storage technology (EST) for small-scale renewable energy systems. The present study was able to achieve this using the results that were generated from a Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and a fuzzy quality function deployment (FQFD) model. Using the FQFD model, experts' opinions were incorporated into the framework during the evaluation of the techno-economic requirements importance for the selection process. The FQFD model considered system safety, availability, flexibility, reliability and effectiveness as customers’ requirements, while nominal voltage, nominal discharge current, peak measured voltage, operating cost and cost of energy were among the techno-economic requirements. During the framework application, a questionnaire was used to collect information from experts on the techno-economic requirements importance, while information on the techno-economic (eleven) requirements for four ESTs were obtained from literature. The FQFD model results were incorporated into a PROMETHEE and TOPSIS models. The PROMETHEE and the TOPSIS models identified Lithium-Ion EST as the best EST for small-scale renewable energy systems.

The purpose of this paper is to explore the influence of ICT on construction supply chain management (CSCM). Furthermore, this research proposes a model for ICT that can be used to test and improve CSCM within the Nigerian construction industry. The relationship between ICT and CSCM was highlighted in an integrated model. Structural equation modelling (SEM) was used to validate the hypothesised relationship by evaluating the responses of practitioners working in construction project management related firms using a sample of 214 respondents. The findings of this study show a link between ICT and CSCM on five (5) of the constructs on targeted construction firms engaged in supply chain (SC)-related construction activities in Port-Harcourt, Rivers State, Nigeria. This research is supported by the Technology Organisation and Environment (TOE) Model as a key theory of technology adoption. With an average R2 value, the SEM model is 76%, which is commendable (high). The current study offers an empirical and theoretical explanation of various aspects of ICT and CSCM, particularly in the Nigerian construction industry. As a result, this study adds to the body of knowledge by providing crucial insight into the influence of ICT on CSCM throughout the entire construction supply chain. The knowledge gained will aid industry stakeholders and the government in developing policies that will increase ICT adoption in current practice.

The primary objective of this paper is to consider the influence of perceived usefulness, per-ceived ease of use, business innovativeness and product innovativeness on the adoption of mo-bile commerce. For the model of this study to be tested empirically, data were collected from mobile commerce users in Nigeria. A total of 405 questionnaires were used for the analysis via PLS-SEM. The results of the study revealed a positive and significant relationship between per-ceived usefulness, perceived ease of use, business innovativeness and product innovativeness. The results of this study provide some guides for mobile commerce practitioners.

The growth in renewable energy study has resulted in the expansion of mini-grids projects across different communities in developing countries. However, there is a need to ensure that a suitable business model is selected during the provision of mini-grid services in developing countries. This study presents a framework for ranking mini-grid business models. The proposed framework is a multi-criteria multi-decision (MCMD) making tool. The framework combines Criteria Importance Through Inter-criteria Correlation (CRITIC), TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) and WASPAS (weighted aggregated sum product assessment) methods. An interval type-2 fuzzy sets (IT2FSs) is used to convert the responses from decision-makers into crisp values. The applicability of the proposed framework was tested using Nigeria as a case study. Four potential mini-grid (private, government, community-based and public-private) business models for the case study were ranked using twelve criteria. The average values for the subjective and objective weight methods showed that electricity traffic and energy demand were the least and the most important criteria, respectively, for selecting a mini-grid business model. The results obtained showed that the best mini-grid model was a private model using a TOPSIS framework. A WASPAS framework ranked the community-based business model as the best model. This study results showed mini-grid business models in developing countries should be either private or community-based business models.