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The purpose of this study is to examine the impact of sustainable supply chain management (SSCM) practices on both competitive advantage (CA) and organizational performance (OP) in the manufacturing sector in Ethiopia.

Data for the study were collected from a sample of 221 manufacturing companies operating in the four manufacturing groups/sectors in Ethiopia. In addition, data analysis was performed using the partial least squares method, which is a variance-based Structural Equation Modeling approach in the Smart-PLS software version (SmartPLS 4.0).

Based on the statistical analysis of the collected data, it demonstrates that SSCM has a significant and positive impact on both competitive advantage and organizational performance. Furthermore, statistical findings offer proof of the clear connection between competitive advantage and organizational performance. Moreover, competitive advantage indirectly mediates the relationship between SSCM and OP.

The primary limitation of this research is its reliance on a cross-sectional design. The generalizability of the findings obtained from the present study may be hindered. The variable under investigation in this research assessed organizational performance, a concept that is widely acknowledged to be extremely dynamic.

The study provides managers and researchers with valuable information on Sustainable Supply Chain Management strategies and how they influence competitive advantage and organizational performance in commercial and industrial environments.

This paper adds to the body of knowledge by providing new data and empirical insights into the relationship between SSCM practices and the performance of manufacturing companies in Ethiopia.

The main objective of this study is to analyze the mediating role of intellectual capital in the relationship between diversification, financial stability, and efficiency of the banking sector in Ethiopia.

Secondary data for this study was obtained from audited financial statements of 17 Ethiopian commercial banks for a decade starting in 2013. A descriptive and explanatory research design with a quantitative research approach was employed. The seemingly unrelated Hierarchical regression analysis is used to estimate diversification’s effect on banks' financial stability and efficiency, considering the interaction between diversification and intellectual capital as a mediating variable.

The Mediation analysis reveals that asset diversification improves the financial stability of commercial banks when mediated by intellectual efficiency. Investment diversification negatively impacts risk-adjusted return on asset and Z score. Intellectual capital significantly enhances commercial banks' efficiency and financial stability in Ethiopia and mediates the relationship between geographic diversification, financial stability, and efficiency. The mediation analysis also indicates that intellectual capital significantly mediates the relationship between income diversification and efficiency.

This study highlights the importance of intellectual capital and promotes its strategic allocation by management and regulatory bodies to enhance the financial stability and operational effectiveness of the banking industry in Ethiopia.

To the best of the researcher’s knowledge, this study is one of the rare attempts to investigate the mediating role of intellectual capital on the nexus between diversification, financial stability, and efficiency of commercial banks in Ethiopia.

This study delves into the complex realm of consumer behavior by exploring the impact of distinct shopping motives, encompassing status, value and gratification, on store satisfaction within the domain of organic food retail. Moreover, it seeks to decipher the influence of perceptual disparities between male and female patrons on the intricate nexus between shopping experience and consumer loyalty within organic food stores.

A comprehensive dataset comprising responses from 400 participants was gathered and subjected to confirmatory analysis and structural equation modeling. These analytical tools were employed to dissect the data, validate the underlying research framework and unveil critical insights.

The empirical analysis, facilitated by structural equation modeling, substantiates that organic food stores prioritize the organic attribute, primarily centered on healthiness, often to the detriment of broader conceptual and social aspects. This validates the interplay between shopping experience dimensions, customer contentment, loyalty and the intent to revisit. Gender, as a moderator, exerts a discernible influence on these relationships, highlighting distinct shopping behaviors among male and female consumers when gauging the influence of shopping experience dimensions within organic food retail establishments.

The implications of this research resonate deeply within the organic food retail landscape. The insights garnered provide valuable guidance to organic food retailers aiming to enhance their store ambiance and allure, thereby fostering sustained customer satisfaction. This, in turn, augments the propensity for customer loyalty and repeat patronage, a particularly pressing concern in today's fiercely competitive retail milieu. Furthermore, the study carries significant ramifications for organic food producers and governmental entities, outlining a framework for augmenting the value proposition of organic foods in alignment with customer experiential paradigms.

In a milieu characterized by the emergence of novel product categories and industry entrants, the study fills a critical void by investigating customer satisfaction within the broader retail food sector, with specific focus on organic food stores. Moreover, the research embarks on a pioneering exploration of the prospective trajectory of organic food stores in the Indian context, employing a marketing lens and grounded in the theory of needs satisfaction.

The purpose of the study is to determine the factors influencing the job choices of Indian women working in the informal manufacturing sector. The informal sector has always played a significant role in emerging and developing countries. This study investigates the effect of social cultural norms influencing women informal workers in the manufacturing sector to participate in home-based work (HBW) or non-home-based work (non-HBW) .

Both Quantitative and Qualitative methodology have been used. In accordance with descriptive statistics, a multinomial logistic regression model was employed to assess women's likelihood of participation in home-based activities. To gain a more in-depth insight, semi-structured interviews were used to collect the perspectives of both men and women workers. The data were analysed using narrative analysis.

The findings reveal that a high fixed cost is a key driver of HBW. Workers prefer to work from home when the loss of joint household production due to working outside is substantial. Social and cultural standards play a significant effect in job selection for women. These conventions limit women's employment options, and the current study demonstrates that strong social and cultural standards limit women to home-based jobs only.

Enhancing women's involvement in the public realm is critical and may be accomplished by affirmative action; but, for women to be treated equally in their homes and in society, an attitude shift is necessary. Despite the government's initiatives and regulations aimed at protecting informal women workers, many of the programmes and legislation fall short. The position of women in this environment cannot be improved until and unless the norms of society are flexible and liberal for Indian women. The first step would be to educate people and make them aware of the need to abandon outdated practices and embrace new progressive ideals. It will not be achievable just via government efforts; rather, both the government and society must work together to achieve the same goal.

The author hereby declares that this submission is their own work and to the best of their knowledge it contains no materials previously published or written by another person, except where due acknowledgement is made in the thesis. The author would like to undertake the above-mentioned manuscript has not been published elsewhere or under editorial review for publication elsewhere; and that all co-authors have agreed to have seen and approved the manuscript for submission.

Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? The purpose of this study is to proposing a methodology to to answer this question that: How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks.

First, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, a new data envelopment analysis (DEA) model is proposed for project selection process. A real example is resolved by the presented model. Finally, the authors use linear discriminate analysis (LDA) to examine the validity of obtained results from the proposed model.

The results show that the proposed model is a suitable tool for selecting Six Sigma Projects. The findings demonstrate that the selected projects by suggested integrated DEA model are those confirmed by LDA.

The paper, using a real case study, provides a mathematical model to enhance decision quality in Six Sigma project selection. Applying the specific DEA model is remarkable itself, which joined to a pioneering procedure to use LDA to validity evaluation of the results.

This research explores the complex interplay of multiple social factors with regard to what might encourage or inhibit users to interact with social commerce (SC).

To investigate the phenomenon, we developed a model based on goal-directed behaviour and pluralistic ignorance theory (typically generated by universal behavioural adherence to social norms). Based on the 394 valid responses collected from a survey, partial least squares structural equation modelling (PLS-SEM), PROCESS and ANOVA were employed to examine the research hypotheses.

The results show that pluralistic ignorance and commercial desire positively influence SC intention. More importantly, our results show that the moderating effect of pluralistic ignorance dampens the positive relationship between social subjective norms and commercial desire. The findings also suggest that pluralistic ignorance mediates the relationships between: (1) social identity and SC intentions and (2) fear of isolation and SC intentions.

Consequently, this study reveals that SC intentions result from complex interactions between an individual’s psychology and social phenomena. Theoretical and managerial implications are also discussed to provide for the successful development of strategies regarding SC for researchers and SNSs operators.

The purpose of this paper is to develop a theoretical model to explain the impact of big data and predictive analytics (BDPA) on sustainable business development goal of the organization.

The authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.

The statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support for H4. Although the authors did not find support for H4 (moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.

This study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.

The purpose of this study is to explore the principal research query and whether strategic foresight deployed by entrepreneurial firms in energy transition aims at crafting future readiness.

With a focus on entrepreneurial firms working in the alternative energy segment in the Indian context, the intent is to examine the deployment of strategic foresight by incumbent firms and their entrepreneurial journey. The authors have adopted the approach of Eisenhardt for this research. The area of interest for the authors entailing strategic foresight by entrepreneurial firms in energy transition aligns with defining features reflecting the aim of Eisenhardt method for this exploratory research coupled with constructivism.

While the future scenarios in the energy sector have to be necessarily multiple, their alignment with different geographic, economic, demographic and political outlooks shall be defined by the pathways niched through the deployment of strategic foresight for arriving at those scenarios.

Strategic foresight deployed by entrepreneurial firms has the potential to create future readiness through self-reliant sustainable economic value chains for local populace, thus propagating holistic development in remote regions.

This paper attempts to knit together the domains of strategic foresight, entrepreneurial firms and energy transition through case research and present the future thinking deployed for navigation in uncharted pathways by capturing the foresight component of these incumbent firms chosen through careful case selection. The narrative has been strengthened by the varied interviews across participants and the observations made by the authors during the research work.

This study aims to propose a competitor intelligence and analysis (CIA) model that can be used for the analysis of a firm’s competitors. Empirically, it investigates the application of the CIA model on online reviews. This proposed model clarifies the confusion between terms such as competitive intelligence, competitor intelligence and competitor analysis and provides a more efficient process for managers.

The approach of the model integrates text mining techniques as a big data method with network analysis to form a competitor analysis. This study has considered two centrality metrics – degree centrality and betweenness centrality – to identify the functional associations among the resources elaborated by the customers of the hotels.

Findings show online reviews may be used as a solid source of intelligence. The intelligence maps visualized through the text-net technique is an efficient representation of tourist satisfaction and dissatisfaction with a tourism company and its competitors.

The proposed approach can be used in the hotel industry along with many others. The implications for scholars and managers and the possible directions for future research are also discussed in the study.

This study develops a new approach for competitive intelligence practices in the hotel industry and tests a new method for competitor analysis as a part of the competitive intelligence and analysis approach developed in this study.

本研究提出了一个竞争对手情报与分析(CIA)模型, 可用于分析企业的竞争对手。对CIA模型在网络评论中的进行了实证研究。该模型厘清了竞争情报、竞争对手情报和竞争对手分析等术语之间的概念混淆, 为管理者提供了一个更有效的流程。

该模型将文本挖掘技术作为大数据方法与网络分析相结合, 来进行竞争对手分析。本研究考虑了两个中心性指标——度中心性和中介中心性——来识别酒店客户精心设计的资源之间的功能关联。

结果表明, 在线评论可被用作可靠的情报来源。情报地图通过文本网络技术可视化有效地展示了游客对旅游公司及其竞争对手的满意度和不满意度。

本文所提出的方法可用于酒店行业及许多其他行业。同时, 本文也探讨了本研究对学者与管理者的启示, 以及未来可能的研究方向。

本文提出了一种新的酒店行业竞争情报的实践方法, 并测试了一种新的竞争对手分析法, 作为竞争情报和分析方法的一部分。

关键词 竞争情报, 竞争对手情报, 文本挖掘, 网络分析, 在线评论, 酒店

Este estudio propone un modelo de análisis de la inteligencia competitiva (CIA) que puede utilizarse para el análisis de los competidores de la empresa. Empíricamente, investiga la aplicación del modelo de la CIA a las reseñas on line. El modelo propuesto aclara la confusión entre términos como inteligencia competitiva, inteligencia de la competencia y análisis de la competencia y proporciona un procedimiento más eficiente para los gerentes.

El enfoque del modelo integra las técnicas de minería de textos, como método de Big Data, con el análisis de redes para realizar el análisis de la competencia. En este estudio se han considerado dos métricas de centralidad -centralidad de grado e intermediación- para identificar las asociaciones funcionales entre los recursos elaborados por los clientes de los hoteles.

Los hallazgos muestran que las reseñas on line pueden ser utilizadas como una fuente sólida de inteligencia. Los mapas de inteligencia visualizados mediante la técnica de redes de texto son una representación eficiente de la satisfacción e insatisfacción de los turistas con la empresa turística y sus competidores.

El enfoque propuesto puede utilizarse en la industria hotelera junto con otros muchos. En el estudio también se analizan las implicaciones para los investigadores y los gerentes y las posibles directrices para investigaciones futuras.

Este artículo desarrolla un nuevo enfoque para la aplicación de la inteligencia competitiva en la industria hotelera y prueba un método nuevo para el análisis de la competencia como parte del enfoque del Análisis de la Inteligencia Competitiva desarrollado en este estudio.

Palabras clave Inteligencia competitiva, Inteligencia del competidor, Minería de textos, Análisis de redes, Reseñas on line, hoteles