Search results

Inventory is a crucial part of a systematic supply chain of a business. Small firms mostly neglect inventory management (IM) by accumulating excessive inventory for a time. The study aims to examine the IM practices of small and medium enterprises (SMEs) in Bangladesh.

The study applied a qualitative case study design. Data were collected from ten SME owners in Bangladesh. The study employed a purposive sampling technique to collect data. This study used semi-structured interviews to generate data. The NVivo software was used to analyze the data.

The findings show that most SME business owners collect raw materials from the local market. Along with the local sources, they collect raw materials from international markets. Some SME entrepreneurs collect raw materials throughout the country as they dealt with recycled products. Frequently, they used digital technologies and online media to manage raw materials. SME owners could not buy many raw materials due to financial crisis, wastage, and damage, leading to a ratio of 10–15% losses.

This research contributes greatly to the government, SME Foundation, and trade associations concerning the SME IM system. The study recommends the government should reduce the tax rate on importing SME raw materials and inventories and exporting SME products.

This is the first study that focuses on the IM systems of SMEs in Bangladesh.

Based on resource dependence theory (RDT) and transaction cost theory (TCT), we aim to investigate the relationship between supply chain concentration and firm performance. Based on the resource-based perspective, we further investigate the moderating effect of marketing and operational capabilities on the relationship between supply chain concentration and firm performance.

Based on data from 2,082 firms with 8,371 observations from 2008 to 2020 in China, we use stochastic frontier analysis to calculate marketing capability and operational capability and use multinational regressions to test our research model.

We find a U-shaped relationship between supplier concentration and firm performance; there is also a U-shaped relationship between customer concentration and firm performance. In addition, the relationship between supplier concentration and firm financial performance is strengthened by the firm’s marketing capability, and the relationship between customer concentration and firm financial performance is weakened by the firm’s operational capability.

Drawing from RDT and TCT, this study extends the research on the impact of supply chain concentration on firm performance. The study finds that supply chain concentration and firm performance have a nonlinear relationship, and it is further moderated by marketing capability and operational capability, providing insights for managers.

The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.

The network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.

The selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.

This study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.

In this study, the central objective is to foresee stock market signals with the use of a proper structure to achieve the highest accuracy possible. For this purpose, three hybrid models have been developed for the stock markets which are a combination of support vector machine (SVM) with meta-heuristic algorithms of particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).All the analyses are technical and are based on the Japanese candlestick model.

Further as per the results achieved, the most suitable algorithm is chosen to anticipate sell and buy signals. Moreover, the authors have compared the results of the designed model validations in this study with basic models in three articles conducted in the past years. Therefore, SVM is examined by PSO. It is used as a classification agent to search the problem-solving space precisely and at a faster pace. With regards to the second model, SVM and ICA are tested to stock market timing, in a way that ICA is used as an optimization agent for the SVM parameters. At last, in the third model, SVM and GA are studied, where GA acts as an optimizer and feature selection agent.

As per the results, it is observed that all new models can predict accurately for only 6 days; however, in comparison with the confusion matrix results, it is observed that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the data for stock market of the years 2013–2021 were analyzed; the long length of timeframe makes the input data analysis challenging as they must be moderated with respect to the conditions where they have been changed.

In this study, two methods have been developed in a candlestick model; they are raw-based and signal-based approaches in which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

This study constructs an efficiency evaluation framework for assessing the human, structural and relational capital in the semiconductor industry of Taiwan. Furthermore, we analyze whether there are significant differences in efficiency across different levels concerning the industry supply chain (upstream, midstream and downstream), employee service tenure, capital scale and company establishment years.

This study focuses on Taiwanese semiconductor companies, utilizing data sourced from the Taiwan Economic Journal (TEJ) Database for the period spanning 2017 to 2021, encompassing a total of five years. Due to the nondisclosure of intangible asset values by all companies, an effort was made to ensure a comparable baseline by excluding companies with incomplete or missing data. Finally, empirical analysis was conducted on a sample of 64 companies using the dynamic network data envelopment analysis method.

(1) Overall efficiency demonstrates structural capital as the most prominent, followed by relational capital, while human capital shows relatively poorer efficiency. (2) To enhance the efficiency of intellectual capital, priority should be given to improving the efficiency of outputs related to intellectual property rights such as patents. (3) The midstream segment exhibits the best efficiency in both structural and relational capital. (4) Companies with longer employee service tenures exhibit superior efficiency in human capital in the long run. (5) Companies with extended establishment years and larger capital scales demonstrate superior efficiency in both human and structural capital.

Reflecting on past literature, scholars have primarily focused on the relationship between intellectual capital and firm efficiency, often emphasizing the overall efficiency of intellectual capital. However, within organizations, human capital, structural capital, and relational capital are interrelated. This study, for the first time, assesses the efficiency of these three components within an organization. The research addresses the challenges in analyzing the efficiency of intellectual capital and introduces a highly contemporary approach – dynamic network data envelopment analysis (DNDEA). Using the semiconductor industry in Taiwan as a case study, this paper conducts empirical analysis in a captivating and worthy industry. Therefore, the ideas presented in this paper are original.

Considering sustainability and resilience together is crucial in food supply chain (FSC) management, as it ensures a balanced approach that meets environmental, economic and social needs while maintaining the system's capacity to withstand disruptions. Towards this, a multi-objective optimisation model is proposed in this study to create an integrated sustainable and resilient FSC. The proposed model employs four objective functions – each representing a dimension of sustainability and one for resilience and utilises an augmented ϵ-constraint method for solving. The findings highlight the interplay between sustainability aspects and resilience, illustrating that overemphasis on any single dimension can adversely affect others. Further, the proposed model is applied to the case of Indian mango pulp supply chain and several inferences are derived. The proposed model would assist decision-makers in making a well-balanced choice based on sustainability and resilience considerations.

The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM), meta-heuristic algorithms, particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).

In addition, among the developed algorithms, the most effective one is chosen to determine probable sell and buy signals. Moreover, the authors have proposed comparative results to validate the designed model in this study with the same basic models of three articles in the past. Hence, PSO is used as a classification method to search the solution space absolutelyand with the high speed of running. In terms of the second model, SVM and ICA are examined by the time. Where the ICA is an improver for the SVM parameters. Finally, in the third model, SVM and GA are studied, where GA acts as optimizer and feature selection agent.

Results have been indicated that, the prediction accuracy of all new models are high for only six days, however, with respect to the confusion matrixes results, it is understood that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the authors to analyze the data the long length of time between the years 2013–2021, makes the input data analysis challenging. They must be changed with respect to the conditions.

In this study, two methods have been developed in a candlestick model, they are raw based and signal-based approaches which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

A relocalization movement, often referred to as neolocalism, is a foot with the aim of rekindling local and regional bonds between people and communities by intentionally and comprehensively crafting senses of place through various promotional strategies. Local-scale businesses often contribute to neolocal efforts through the integration of “place” with their brand development and marketing schemes. Together such efforts converge to form local consumption spaces that foster both economic vibrancy and social cohesion within and across communities. While sometimes recognized as a secondary benefit, environmental stewardship has yet to be fully developed as a neolocal construct and consistent trait of local consumption spaces. In this chapter, an extensive review of the intersection between the environmentalism, neolocalism, and eco-entrepreneurship literature is used to conceptually frame the notion of eco-consumption spaces. The insights generated lead to a proposed research agenda that includes recommendations pertaining to both empirical settings and methodological strategies.

This research serves to determine causal configurations of corporate social responsibility (CSR) conditions that best influences grassroots football club stakeholders to meet a sponsor's goals through promotional activity.

The research uses a case study of the Essex Alliance League, a local amateur football league in England. Firstly, semi-structured interviews were held with multiple stakeholders to understand the ecosystem of grassroots football. From here, further semi-structured interviews were held with club sponsors to identify the conditions of CSR. This allowed the research to then issue a survey from which results were analysed and discussed using fuzzy set Qualitative Comparative Analysis (fsQCA).

The ecosystem of grassroots football is formed by a myriad of stakeholders operating at a national level, all the way to more local governance structures within which the business-club relationship exists. Sponsors identified three main conditions of CSR: shared values, self-congruity, and happiness. However, following fsQCA, two pathways were found: (1) presence of shared values, and (2) presence of happiness with the absence of self-congruity.

For practitioners, adaptations can be made for clubs to attract and maintain sponsorship as businesses seek to use grassroots sport as a channel for their own CSR objectives. To attract long term sponsorship, club managers are recommended to maintain long-term relationships with business owners especially in relation to personal values, fit, and happiness. As such, the responsibility of the club to ensure its stakeholders engage in promotional activity on behalf of their sponsor will help in maximising the financial value over multiple seasons.

Where fertile ground for academic analysis in grassroots football is present, this research investigates CSR activity at this level of football, where most research is more concerned with professional levels of the game. Furthermore, this research reaches into the sport ecosystem through an understanding of co-created values between organisations in this exchange of shared values to meet common objectives.

This study systematically explores the literature on global niche market strategies within the fashion industry to allow the mapping of niche practices and examine the benefits, success factors and characteristics of a niche strategy. Additionally, it identifies data gaps and necessitates a detailed examination to uncover areas with inadequate information.

This study utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 2020) method for systematic review and included 70 studies to analyze their findings.

This systematic literature review pinpoints niche strategies shaping the future of the fashion industry while developing sectors of the textile and apparel industry, fashion technology, fashion retail business, fashion media and communication, luxury fashion, sustainable fashion, adaptive clothing and transgender fashion within the fashion supply chain. A niche market strategy utilizes both pull and push marketing in the fashion industry. Scholarly literature commonly underscores the understanding of the consumer as a pivotal factor in the success of fashion niche market strategy.

This review offers a comprehensive overview of fashion niche strategy practices, aiming to inspire fashion industry professionals. It also serves as a guide for fashion industry professionals, summarizing best practices across various fashion industry sectors to help develop effective niche strategy competencies for firms.

This review thoroughly analyzes niche strategy implementation in the fashion industry, presenting an important resource for individuals new to this sector. It highlights the significance of niche strategies in improving the comprehension of emerging participants in the fashion business.