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The innovativeness of dressmakers is a concern to respondents to satisfy their clothing needs. The purpose of this study is to determine the criteria that respondents use to judge the quality of clothing and its influences on the innovative ability of dressmakers in the clothing manufacturing industries.

Three hundred and ninety-seven (397) respondents in the Takoradi Metropolis of Ghana filled out a questionnaire, and the results were used to compile data for the study. The sample size was calculated using Miller and Brewer formula. The data was analysed using structural equational modelling with the SmartPLS v.4 software.

The results showed that respondents are very interested in the calibre of clothing produced by their dressmakers. However, the study revealed that when evaluating the quality of a garment, respondents do not simply accept what has been sewn for them but also consider the performance, appearance, fit and shape of the garment. Findings revealed that there was a significant relationship between garment appearance quality (t = 2.605; p < 0.05), garment performance quality (t = 3.915; p < 0.05), garment shape quality (t = 6.248; p <0.05) and fashion innovations. Subsequently, the evaluation of garment fit quality by respondents revealed it does not bring about innovations (t = 1.310; p > 0.05).

The continuous evaluation of custom-made clothing from customers will go a long way towards highlighting the relative criteria they use to evaluate the innovation of dressmakers. This will help improve the creativity of the dressmakers since such feedback will help them understand and innovate their production skills to meet the preferences of customers.

The present study provides an in-depth understanding of how garment quality evaluation by customers influences the innovation of dressmakers in Takoradi, Ghana. The constructs were developed for the study to capture the appropriate data from customers for the study. This presents an evaluation criterion on four garment quality variables imperative for use or modification by other studies.

The purpose of this study is to investigate the physical, ultraviolet (UV), colour appearance and colour fastness properties of selected fabrics dyed with natural dyes from Daboya and Ntonso communities of Ghana. The study further highlights the rich cultural heritage of traditional dyeing from these two communities. Craftsmen in West Africa especially Ghana, have sustained the traditional dyeing methods to produce textile products for consumers.

In this study, two sample fabrics were purchased from craftsmen at Ntonso and Daboya communities in Ghana. These fabrics were analysed at the laboratory under standard test methods for their physical, UV, colour appearance and colour fastness properties.

Results showed that all the sample fabrics have good UV shielding performance (ratings above 50+). Daboya sample fabrics (dyed with indigo dyes) produced more colour stains than the sample fabrics from Ntonso (dyed with black “kuntunkuni” dyes). The K/S_sum value or colour yield reduced after washing but that alternatively increased the calculated ultraviolet protection factor.

Findings from this study exposed the unique UV performance of dyed traditional fabrics (using natural dyes) from Ntonso and Daboya communities in Ghana. This inspires and enforces the need for craftsmen to improve their production cycle to produce these fabrics in different sizes which provides the necessary UV shielding abilities for consumers in the wake of climate changes.

This study demonstrated that the natural dyeing process at the two communities produced relatively good UV and colour fastness properties of the sample fabrics. These eco-friendly dyeing practices have survived over time to maintain and promote the concept of sustainability within the textile and fashion industry in Ghana.

The purpose of this study is to present a systematic review of the effects of COVID-19 on the conventional textile production subsector. The emergence of the COVID-19 virus in 2019 has subsequently caused many problems, such as unemployment, business closures, economic instability and high volatility in the global capital markets amongst others within the wider manufacturing industry including textile production.

Relevant secondary data are obtained from the Scopus database and Statista. Based on the data analysis of 21 seed articles, three research themes are identified: challenges in the textile industry, new material innovations or solutions and the textile industry performance.

The results reveal that the COVID-19 pandemic has affected the textile industry, disrupted the supply chains of this industry, affected profit margins, stopped employment and impacted the retail of products to customers. Aside from the negative repercussions, there are also good sides to the pandemic which, for instance, range from advanced material innovations to textiles with anti-microbial, self-cleaning and anti-bacterial properties that would limit the transfer of the virus.

Findings reinforced the need for effective strategies and investments in the research and development departments of the various firms in the textile industry to innovate operations and novel materials for the next global pandemic.

Many companies have adopted novel strategies and practices that are helping them to survive the pandemic. This study, therefore, recommends further investigation into material innovations and reimagining strategies by companies and the supply chain within the textile industry so that it is protected against future crises.

Digital platforms increase their function and scope by leveraging boundary resources and complementary add-on products from third-party developers to interact with external entities and producers. Application Programming Interfaces (APIs) are essential boundary resources developers use to connect applications, systems and platforms. This notwithstanding, previous API studies tend to focus more on the technical dimensions, with little on the social and cultural contexts underpinning API innovations. This study relies on the new (neo) institutional theory (focusing on regulative, normative and cultural-cognitive pillars) as an analytical lens to understand the institutional forces that affect API integration among digital firms.

The study adopts a qualitative case study methodology and relies on phone calls and a semi-structured in-depth interview approach of a Ghanaian digital music platform to uncover the institutional forces affecting API integration.

The findings reveal that regulative institutions such as excessive tax regimes mostly constrained API development and integration initiatives. However, other regulative institutions like the government digitalization agenda enabled API integration. Normative institutions, such as the growing use of e-payment options, enabled API integration in digital music platforms. Cultural-cognitive institutions like employee ego constrained the API integration process in music digital platforms.

This study primarily contributes to deepening understanding of the relevant literature by exploring the institutional forces that affect API integration among digital firms in a developing economy. The study also uncovered a new form of an institution known as motivational institution as an enabler for API development and integration in digital music platforms.

Heuristics are used in the judgment and decision-making process of bank employees; however, discussions and research on the type or range of judgmental heuristics are very difficult to find throughout the world. In light of this, the purpose of this paper is to empirically analyze what types of heuristics are used in bank employees’ judgment and decision-making processes and the extent to which those types of heuristics prevent rational decision making due to the systematic biases they generate. In particular, this study aims to conduct empirical research based on various scenarios related to the banking industry.

To examine the heuristics in decision-making circumstances and the level of subsequent biases, the present study narrowed the scope of research to the three main types of heuristics introduced by Tversky and Kahneman (1974), namely, representativeness heuristics, availability heuristics and anchoring and adjustment heuristics. To analyze the bank employees’ decision making, this study specifically investigated the level of decision-making heuristics and the level of bias by focusing on these three types of heuristics. This study targeted bank employees who either sell financial products or are engaged in customer service work at a real/physical bank.

For representativeness heuristics, this study found bank employees’ judgment of probability was influenced by biases, such as insensitivity to prior probability, insensitivity to sample size, misconception of chance and insensitivity to predictability. Regarding availability heuristics, it found that bank employees judge the probability of events based on the ease of recalling an event instead of the actual frequency of the event, and so they fall prey to systematic biases. Finally, regarding anchoring and adjustment heuristics, this study found that employees fall prey to judgment biases as they judge the probability of conjunctive events and disjunctive events based on anchoring and insufficient adjustment.

Although people who are well-trained in statistics can avoid rudimentary errors, they fall prey to biased judgment at a similar level to those who are not properly trained in statistics when it comes to more complicated and ambiguous issues. It clearly indicates that it is risky to determine that financial experts would be more rational than the general public in making various judgments required in the policy-making process. To conclude, it is imperative to recognize the existence of heuristics-based systematic biases in the judgment and decision-making process and, furthermore, to reinforce the education and training system to improve bank employees’ rational choice and judgment ability.

The purpose of this study is to investigate the roles of perceived usefulness, top management support and information technology (IT) infrastructure in developing user satisfaction and loyalty in the context of smart factory.

This study gathered the data through a survey of 161 smart factory workers in South Korea. A partial least squares analysis was used to test the measurement and structural models.

The results show that perceived usefulness positively influences satisfaction. In addition, IT infrastructure significantly affects both satisfaction and loyalty. Finally, system quality has a positive impact on perceived usefulness.

IT infrastructure facilitates the level of satisfaction and loyalty. System quality enhances the satisfaction via perceived usefulness. Researchers need to examine the nature of IT infrastructure and system quality that will foster satisfaction and loyalty. Future studies can examine the segmented constructs of IT infrastructure to understand the role of IT infrastructure more comprehensively.

Firms should invest more in IT infrastructure and pay attention to elevate the level of system quality of smart factory. This research provides managers with guidance concerning how IT infrastructure of firms and system quality of smart factory have positive effects on satisfaction and loyalty.

This study contributes to the extant literature on information system (IS), project management, organizational innovation and industrial marketing. This research incorporated system factors, top management support and IT infrastructure to understand satisfaction and loyalty of IS users in the context of smart factory. The findings offer a useful view for integrating insights from different research streams.

Anthropogenic activities such as unsustainable consumption pattern is one of the reasons responsible for the ongoing environmental issues. Although, consumers are becoming increasingly aware and concerned about environmental problems their attitudes are not resulting in sustainable consumption behavior (SCB). Celebrity institutional entrepreneurs can engage and inspire the public at large and contribute to institutional change. Hence, this study aims to explore the potential of celebrity institutional entrepreneurship in galvanizing mainstream SCB by increasing the awareness of environmental issues and their consequences.

This study examines the actor's influence by conducting a netnographic analysis of Leonardo DiCaprio's Instagram account. Further, qualitative interviews of account followers were also conducted to evaluate the influence of account on their awareness levels and consumption practices.

Our findings indicate that account had a significant impact on consumers' environmental awareness and engagement with environmental issues. However, a partial impact was seen in case of their sustainable consumption practices. Our study concludes that celebrity institutional entrepreneurship can help in addressing the attitude-behavior gap in sustainability research.

This study is amongst the few studies that attempted to explore the ways to reduce the attitude-behavior gap in SCB. It examines the potential of celebrity institutional entrepreneurship to galvanize mainstream sustainable consumption. The results of this study are useful to key stakeholders (policymakers, marketers, social-environmental groups etc.) in the development of more effective strategies for sustainable development.

This study proposes a methodology based on data source triangulation to measure the “strategic fit” for the automotive supply chain.

At first, the authors measured the responsiveness of the Indian automobile supply chain, encompassing the top ten major automobile manufacturers, using both sentiment and conjoint analysis. Second, the authors used data envelopment analysis to identify the frontiers of their supply chain. The authors also measured the supply chain's efficiency, using the balance sheet. Further, the authors analyzed the “strategic fit” zone and discussed the results.

The results indicate that both the proposed methods yield similar outcomes in terms of strategic fitment.

The study outcomes facilitate measuring the strategic fit, thereby leveraging the resources available to align. The methodology proposed is both easy to use and practice. The methodology eases time and costs by eliminating hiring agencies to appraise the strategic fit. This valuable method to measure strategic fit can be considered feedback for strategic actions. This methodology could also be incorporated possibly as an operative measurement and control tool.

Data triangulation meaningfully enhances the accuracy and reliability of the analyses of strategic fit. Data triangulation leads to actionable insights relevant to top managers and strategic positioning of top managers within a supply chain.

This paper aims to review analogical reasoning work to distil and apply procedural guidelines that aid theoreticians to develop novel analogies.

The authors reviewed 189 studies from 1980 to 2020 to identify analogical reasoning guidelines.

Results revealed four procedural steps for the introduction of novel analogies: target and source domain selection; domain image mapping; relevance assessment; and proposition drafting. […] shallow lakes constitute the source domain and sustainable supply chain management represents the target domain.

The identified procedural guidelines can help future scholars to develop novel analogies with rigor and structure. The paper provides an agenda for new research that addresses gaps in current studies that reason by analogy.

This paper distils and applies analogical reasoning guidelines for the development of novel analogies, extending and complementing much existing theorizing on reasoning by analogy. Additionally, disjointed and fragmented research findings are synthesized to yield a comprehensive understanding of analogical reasoning, which can serve as a foundation for future theorizing in sustainable supply chain management and beyond.

The authors develop a methodology to select appropriate sustainable supply chain indicators (SSCIs) to measure Sustainable Development Goals (SDGs) in the global supply chain.

SSCIs are identified by reviewing the extant literature and topic modeling. Further, they are evaluated based on existing SDGs and ranked using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Notably, the evaluation of indicators is a multi-criteria decision-making (MCDM) process within a fuzzy environment. The methodology has been explained using a case study from the automobile industry.

The case study identifies appropriate SSCIs and differentiates them among peer suppliers for gaining a competitive advantage. The results reveal that top-ranked sustainability indicators include the management of natural resources, energy, greenhouse gas (GHG) emissions and social investment.

The study outcome will enable suppliers, specialists and decision makers to understand the criteria that improve supply chain sustainability in the automobile industry. The analysis provides a comprehensive understanding of the competitive package of indicators for gaining strategic advantage. This proactive sustainability indicator selection promotes and enhances sustainability reporting while fulfilling regulatory requirements and increasing collaboration potential with trustworthy downstream partners. This study sets the stage for further research in SSCIs’ competitive strategy in the automobile industry along with its supply chains.

This study is unique as it provides a framework for determining relevant SSCIs, which can be distinguished from peer suppliers, while also matching economic, environmental and social metrics to achieve a competitive advantage.