Search results

Effective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.

The basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.

The study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.

The study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.

The RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.

Warranty-based big data analysis has attracted a great deal of attention because of its key capabilities and role in improving product quality while minimizing costs. Information and details about particular parts (components) repair and replacement during the warranty term, usually stored in the after-sales service database, can be used to solve problems in a variety of sectors. Due to the small number of studies related to the complete analysis of parts failure patterns in the automotive industry in the literature, this paper focuses on discovering and assessing the impact of lesser-studied factors on the failure of auto parts in the warranty period from the after-sales data of an automotive manufacturer.

The interconnected method used in this study for analyzing failure patterns is formed by combining association rules (AR) mining and Bayesian networks (BNs).

This research utilized AR analysis to extract valuable information from warranty data, exploring the relationship between component failure, time and location. Additionally, BNs were employed to investigate other potential factors influencing component failure, which could not be identified using Association Rules alone. This approach provided a more comprehensive evaluation of the data and valuable insights for decision-making in relevant industries.

This study's findings are believed to be practical in achieving a better dissection and providing a comprehensive package that can be utilized to increase component quality and overcome cross-sectional solutions. The integration of these methods allowed for a wider exploration of potential factors influencing component failure, enhancing the validity and depth of the research findings.

This study aims to empirically analyze the impact of technological innovation on the quantity and quality of employment in the hospitality industry.

Using the data of 30 provinces in China from 2010 to 2020, this paper makes an empirical analysis through the fixed effect model.

The results show that process innovation has a significant positive impact on employment quantity, while product innovation has a significant negative impact on employment quantity. The creative effect of process innovation and the substitution effect of product innovation offset each other, so in the long run, the impact of technological innovation on employment quantity is not significant. However, technological innovation has significantly improved the employment quality of the hospitality industry.

Because technological innovation has replaced part of the labor force, hospitality could guide the labor force in a positive direction. To promote innovation and retain talents, hotels should train employees’ digital thinking and attract high-skilled talents.

This research is unique in using process innovation and product innovation as the main measurement indicators of technological innovation, unlike previous studies that often relied on technological progress to conclude.

Under the carbon tax policy, the authors examine the operational decisions of the low-carbon supply chain with the triple bottom line.

This paper uses the Stackelberg game theory to obtain the optimal wholesale prices, retail prices, sales quantities and carbon emissions in different cases, and investigates the effect of the carbon tax policy.

This study’s main results are as follows: (1) the optimal retail price of the centralized supply chain is the lowest, while that of the decentralized supply chain where the manufacturer undertakes the carbon emission reduction (CER) responsibility and the corporate social responsibility (CSR) is the highest under certain conditions. (2) The sales quantity when the retailer undertakes the CER responsibility and the CSR is the largest. (3) The supply chain obtains the highest profits when the retailer undertakes the CER responsibility and the CSR. (4) The environmental performance impact decreases with the carbon tax.

The results of this study can provide decision-making suggestions for low-carbon supply chains. Besides, this paper provides implications for the government to promote the low-carbon market.

Most of the existing studies only consider economic responsibility and social responsibility or only consider economic responsibility and environmental responsibility. This paper is the first study that examines the operational decisions of low-carbon supply chains with the triple bottom line under the carbon tax policy.

The main aim of this study is to explore the appropriate factors in measuring COVID-19-induced supply chain disruptions and the impact of these disruptions on the economic vulnerability of small-scale farmers in Sri Lanka.

The findings revealed that most of the farmers have continued to cultivate even during the pandemic despite several challenges which affected their economic status. Therefore, it is concluded that COVID-19-induced transportation and demand disruptions exacerbated the economic vulnerability of small-scale farmers over the disruptions in supply and production.

The findings of this study are crucial for formulating novel policies to improve the sustainability of the Sri Lankan agricultural sector and alleviate the poverty level of Agri-communities in the countryside. As farming is a vital sector in the economy, increased attention ought to be given on facilitating farmers with government-encouraged loans or allowances for their financial stability. Further, the respective government authorities should develop programs for importing and distributing adequate quantities of fertilizers among all the farmers at controlled prices so that they can continue their operations without any interruption. Moreover, the government could engage in collaboratively work with private organizations to streamline the Agri-input supply process. There should be a government initiative for critical consideration of the issues of farming families and their continued motivation to engage in agriculture. Thus, farmers' livelihoods and agricultural prosperity could be upgraded through alternative Agri-inputs and marketing strategies, providing financial assistance, encouraging innovative technology, etc.

Despite the significance and vulnerability of the vegetable and fruit sector in Sri Lanka, there is a limitation in the empirical studies conducted on the supply chain disruptions caused by COVID-19 measures and their implications on the farmers' livelihood. Furthermore, previous empirical research has not employed adequate quantitative tools to analyze the situation or appropriate variables in evaluating COVID-19-induced disruptions. Hence, the current study explored the appropriate factors for measuring COVID-19-induced supply chain disruption using exploratory factor analysis. Then, the impact of those factors on the economic vulnerability of the small scale farmers was revealed through the ordinal logistics regression analysis.

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

This paper aims to examine the level of economic efficiency and factors that influence economic efficiency among seed potato producers in South-western Uganda.

The paper analyses the economic efficiency of 499 informal and 137 formal seed producers using primary data collected through a structured questionnaire. A multi-stage sampling technique was used to select the study sites and specific farmers. A one-step estimation procedure of normalized translog cost frontier and inefficiency model was employed to determine the level of economic efficiency and the influencing factors.

The results showed that mean economic efficiencies were 91.7 and 95.2% for informal and formal seed potato producers, respectively. Furthermore, results show significant differences between formal and informal seed potato producers in economic efficiency at a one percent level. Market information access, credit access, producers' capacity and experience increase the efficiency of informal while number of potato varieties, market information access and producers' experience increase economic efficiency for formal counterparts.

Most seed potato producers, especially the informal ones do not keep comprehensive records of their production and marketing activities. This required more probing as answers depended on memory recall.

Future research could explore panel data approach involving more cropping seasons with time variant economic efficiency and individual unobservable characteristics that may influence farmers' efficiency to validate the current findings.

The paper shows that there is more potential for seed potato producers to increase their economic efficiency given the available technology. This has a direct implication on the economy through increased investment in the production and promotion of high yielding seed potato varieties to meet the growing national demand for potatoes.

The paper bridges the gap in literature on economic efficiency among seed potato producers, specifically in applying the normalized translog cost frontier approach in estimating economic efficiency in the context of potato sub-sector in Uganda.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2021-0641

The authors assess the development potential of cowpea beyond grain in local markets in Mali by: (1) identifying trader types and types of cowpea products sold; (2) examining trader roles; (3) estimating gross margins and their determinants; and (4) discussing policy opportunities to further develop the value chain.

The authors analyze data collected through observation and semi-structured questionnaires from 487 sellers in 26 markets, including market, seller, and product characteristics. The authors also calculate gross margins and conduct a regression analysis to identify influential factors.

The authors identify several types of cowpea sellers in local markets, including processor-retailers, retailers of fresh leaves and fodder, and grain retailers, collectors and wholesalers. Women dominate the marketing of processed products and fresh leaves. The marketing of boiled cowpeas offers retailers higher margin rates compared to fritters and pancakes. Grain sellers, who are mostly men, have lower margins but sell larger quantities. Processor-retailers bring more value to the cowpea value chain. Specialization of the seller in cowpea, regional location of the market and day of the market fair all influence gross margins.

Future work should explore consumer preferences for different types of cowpea products.

This study of the cowpea value chain in Mali has revealed the multidimensional character of the cowpea plant, which goes far beyond its grain and highlight the important roles played by women.

The purpose of this paper is to ascertain if practising healthy lifestyles improves the technical efficiency of farms in Kwara state, Nigeria. In theory, all deviations from the optimum level of output are due to random effects and inefficiency of producers in which their health plays a key part and is dependent on the kind of lifestyle practiced whether healthy or unhealthy.

Cross-sectional data were employed through a three-staged sampling technique to pick 320 arable crop farmers across the state using a well-defined questionnaire. Data analysis was carried out using descriptive statistics, healthy lifestyles index (HLI), stochastic production frontier (SPF) and propensity score matching (PSM).

First, the analysis showed that about one-third of the sampled arable crop farmers practised healthy lifestyles. Second, the average technical efficiency of arable crop production for farmers who practised a healthy lifestyle was 0.893, and the level of technical inefficiency of the farms was determined by health-related lifestyle status, number of day's illness and educational level. Third, technical efficiency was improved by 0.00431067 for farms whose farmers practised a healthy lifestyle.

Rather than seeing that technical efficiencies of farms are attributed to farm characteristics, inputs used and socioeconomic characteristics alone, the findings suggest that technical inefficiencies of arable crop farmers were also due to the kind of lifestyle practised, which was evidenced in the increased efficiency for farmers who practised healthy lifestyle.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0353