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Fashion products such as clothes, accessories, bags and footwear created using 3D printed technology are referred to as 3D printed fashion (3DPF) products. This study investigates consumers' motivation to purchase 3DPF products. In particular, this study adopts a multi-dimensional approach to explore the effects of personality-related traits such as innate, domain-specific and actualized innovativeness, as well as examine the effects of perceptions toward 3D printing technology (3DPT) (i.e. perceived security risk, performance expectancy). Based on the concepts of consumer innovativeness and the Unified Theory of Acceptance and Use of Technology (UTAUT), the authors expect the effects of consumers' innovativeness and perception of 3DPT and confirm its significant effects on a positive attitude toward 3DPF products and future purchase intention of 3DPF products.

A quantitative research design (i.e. survey) is utilized to examine the suggested relationships and application of existing theory in this study. All measurement items are adapted from previous literature and use a Likert-scale. The authors examined a total of 326 responses using a series of statistical analyses, including descriptive statistics, structural equation modeling and conditional process modeling.

The results of this study confirmed that innate and domain-specific innovativeness are critical antecedents of creating a positive attitude toward using 3DPF products through perceptions toward 3DPT. In addition, 3DPF innovativeness, as actualized innovativeness, was validated to strengthen the relationship between personal innovativeness and attitude, providing evidence that innovation-related traits can predict behaviors. Interestingly, technological innovativeness was not found to be a predictor of perceived security risk. It may be due that 3DPF products are still novel to consumers.

The study participants were people who were interested in technology, not consumers who had prior experience with using 3DPF products. Future studies are encouraged to include consumers who have actually purchased or used 3DPF products.

The findings of this study indicate that consumers' use of new technology is determined by personality and interest in specific product categories. Practitioners may use this information to segment/target consumer groups to introduce a new/unfamiliar product.

The findings of this study contribute to the existing literature on consumer adoption of innovation by combining two approaches, the hierarchy of consumer innovativeness and the UTAUT, in the context of advanced technology adoption behavior.

A humanoid intelligent robot (HIR) possessing a human-like appearance can undertake human jobs, interact, communicate and even transmit emotions to human beings. Such robots have gradually been integrated into people's daily life and production scenarios. However, it is unclear whether and by what mechanism HIRs can stimulate people’s risk perception and its impact on consumption attitudes. Based on the risk decision theory, this study aims to take the social value substitution attribute of a HIR as the incentive and analyzes the influence of social value substitution and risk perception on the customers’ consumption attitudes.

Three experiments were conducted to investigate the related questions about the social value substitution attribute of a HIR, its impact on risk perception and the customers’ consumption attitudes.

The results reveal that physical labor, intellectual labor, friendship, kinship and the ego constitute the hierarchical elements of social value substitution. Among them, physical labor and intellectual labor pertain to the dimension of social function value substitution, while friendship, kinship and ego pertain to the dimension of social presence value substitution; social function value substitution and social presence value substitution affect the subjects’ risk perception positively, but the latter arouses a stronger risk perception; the 2 (risk perception of social function value: security/danger) × 2 (risk perception of social presence value: security/danger) condition corresponds to diverse consumption attitudes.

The results enrich the theories of the “cha-xu pattern” and “uncanny valley” and provide reference for the healthy development of the HIR industry.

This study was carried out to analyze the importance of consumer preference data in forecasting demand in apparel retailing.

To collect preference data, 729 hypothetical stock keeping units (SKU) were derived using a full factorial design, from a combination of six attributes and three levels each. From the hypothetical SKU's, 63 practical SKU's were selected for further analysis. Two hundred two responses were collected from a store intercept survey. Respondents' utility scores for all 63 SKUs were calculated using conjoint analysis. In estimating aggregate demand, to allow for consumer substitution and to make the SKU available when a consumer wishes to buy more than one item in the same SKU, top three highly preferred SKU's utility scores of each individual were selected and classified using a decision tree and was aggregated. A choice rule was modeled to include substitution; by applying this choice rule, aggregate demand was estimated.

The respondents' utility scores were calculated. The value of Kendall's tau is 0.88, the value of Pearson's R is 0.98 and internal predictive validity using Kendall's tau is 1.00, and this shows the high quality of data obtained. The proposed model was used to estimate the demand for 63 SKUs. The demand was estimated at 6.04 per cent for the SKU cotton, regular style, half sleeve, medium priced, private label. The proposed model for estimating demand using consumer preference data gave better estimates close to actual sales than expert opinion data. The Spearman's rank correlation between actual sales and consumer preference data is 0.338 and is significant at 5 per cent level. The Spearman's rank correlation between actual sales and expert opinion is −0.059, and there is no significant relation between expert opinion data and actual sales. Thus, consumer preference model proves to be better in estimating demand than expert opinion data.

There has been a considerable amount of work done in choice-based models. There is a lot of scope in working in deterministic models.

The proposed consumer preference-based demand estimation model can be beneficial to the apparel retailers in increasing their profit by reducing stock-out and overstocking situations. Though conjoint analysis is used in demand estimation in other industries, it is not used in apparel for demand estimations and can be greater use in its simplest form.

This research is the first one to model consumer preferences-based data to estimate demand in apparel. This research was practically tested in an apparel retail store. It is original.

This paper focuses on multi-objective order allocation with product substitution for the vaccine supply chain under uncertainty.

The weighted-sum minimization approach is used to find a compromised solution between three objectives of minimizing inefficiently vaccinated people, postponed vaccinations, and purchasing costs. A mixed-integer formulation with substitution quantities is proposed, subject to capacity and demand constraints. The substitution ratios between vaccines are assumed to be exogenous. Besides, uncertainty in supplier reliability is formulated using optimistic, most likely, and pessimistic scenarios in the proposed optimization model.

Covid-19 vaccine supply chain process is studied for one government and three vaccine suppliers as an illustrative example. The results provide essential insights for the governments to have proper vaccine allocation and support governments to manage the Covid-19 pandemic.

This paper considers the minimization of postponement in vaccination plans and inefficient vaccination and purchasing costs for order allocation among different vaccine types. To the best of the authors’ knowledge, there is no study in the literature on order allocation of vaccine types with substitution. The analytical hierarchy process structure of the Covid-19 pandemic also contributes to the literature.

The category captain system (CC) of retailer category management (RCM) is established, accepted, and widely adopted. The paper empirically assesses the application of this system in building collaborations between retailers and their suppliers to generate growth following COVID-19. This study applies service-dominant logic (S-D logic) to RCM and establishes the current ‘practical’ application of the five axioms of S-D logic within the CC system.

The researchers adopted a qualitative research design which examined both category managers and retail buyers currently involved in the CC system, using thematic analysis of transcripts from 25 practitioner participants.

The study reveals service is not a fundamental basis of exchange in the CC system. Value is uniquely, independently, and separately created by the retailer that significantly restricts the scope of the category service eco systems and the opportunity to innovate through value co-creation.

Significant change is required to realise value co-creation and innovation applying S-D logic to RCM. The study indicates there is potential to start this change by the formalisation of wider informal category relationships between non-captain suppliers and retailers through consumer insight technology, and by aligning suppliers and retailers to make more effective and sustainable trading decisions.

The study indicates that certain elements of the CC system proposed by the literature's games-based theoretic models, are not applied in practice. The lived experiences of practitioners suggest informal ways of by-passing the formal system using S-D logic.

This paper aims to investigate the effects of buzz about the focal brand on competing brands’ attitudes.

Brand-related buzz can be defined as “a general sense of [positive or negative] excitement about or interest in [a brand], as reflected in or generated by word of mouth” (Oxford dictionary). The authors investigate the spillover effects of such positive and negative buzz on brand attitudes of 648 brands in 43 categories over five years.

The authors find that spillover effects are widespread across product categories and affect competing brands through (negative) halo effect and (unfavorable) preference substitution. The authors do not find evidence of positive spillover effects for non-focal brands.

The authors provide generalizable evidence that positive and negative buzz spills over competing brands’ attitudes for hundreds of brands across the largest sectors of the US economy. Interestingly, positive and negative buzz have asymmetric effects on consumer attitudes. These effects vary by consumer attitude metric and are moderated by brand news intensity, strength and similarity.

First, marketing managers should monitor the buzz of competing brands. Second, if managers are concerned with impressions, they should intervene when there is a negative buzz about competitors (halo effect). Third, managers should stimulate positive buzz to negatively affect their competitors’ purchases. Fourth, managing a smaller brand has advantages regarding impressions and recommendations, while news intensity can shield from negative spillover effects for impressions. Finally, brand similarity amplifies the spillover effects across the board.

This paper provides evidence that spillover effects are pervasive and urges marketing managers and academics to incorporate competing buzz in their frameworks and strategies.

The objective of this paper is to study the impact of political connection and governance on credit rating and whether there is a substitution or complementary relationship between them.

In order to achieve the objective, a succession of eight ordered probit regressions has been carried out. Moderating variables between the political connection and governance characteristics were introduced. The whole population is taken as a sample, i.e., 27 Tunisian companies that are evaluated by FITSH NORTH AFRICA agencies over a period of 10 years (2009–2018).

The outcomes are mixed. They show that the political connection does not always influence credit rating; the size and board independence always improves credit rating; the duality between the functions affects credit rating; whereas the majorities’ proportion does not influence credit rating; and a substitution between the political connection and the governance characteristics is validated.

Like any other research, our results are factors of our measures and variable choice and depends heavily on the how these variables were conceived. Also, although our number of observations responds to the statistical result generalization requirements, our sample remains relatively narrow with 27 companies only.

In practice, the research will allow investors to have a better vision upon the future of their investments based on whether to develop their governance system or promote political networking. It will also prompt lenders to look beyond ratings and consider factors such as political connections to make a rational judgment on their future placements.

This study leads us to find various solutions: the establishment of credit agencies that take into consideration all the data of all the operators taken as a whole (bank, leasing company, and factoring). It encourages the reorganization of the Tunisian banking sector through mergers for example.

This study is a pioneer in the credit rating field in Tunisia, where the source of debt financing is the most used by all enterprises across all sectors. This study extends the literature of political connection effectiveness, independent directors, board size, in improving corporate performance and credit rating.

This article provides evidence of a long-term structural relationship between demand for heated tobacco products (HTPs) and for combustible cigarettes in a Marshallian demand framework, using data from the Italian market.

A cointegration-based approach allows to capture the substitution effects between the two products arising for reasons (possibly) other than price.

The authors find that such a relationship exists and is sufficiently strong to constitute a cointegration.

Since a fully consolidated consensus on reduced harm from smokeless tobacco products is absent, symmetric policies on both markets are therefore necessary in terms of regulation and excise incidence to minimize the social cost of substitution and to maximize government revenues, which are a necessary counterpart to negative externalities that arise with smoking both products.

This paper focuses on the Italian market with product specific volume and price data, both for cigarettes and HTPs. Because of the detected relationship, a regulatory trade-off arises in case of a relatively mild regulation on heated-tobacco products: benefits from decreasing demand for combustible cigarettes may be offset by the social cost of increasing consumption of heated tobacco products. Moreover, a milder regulation makes price related policies to curb smoking less effective.

This study aims to estimate the value of the impact from digital transformation (DX) focusing on its automation effect, looking at the time and cost savings coming from the substitution effect with an adoption of digital technologies. For example, cloud and artificial intelligence technologies such as ChatGPT have the potential to change ways of working, substituting and replacing several of the tasks that are currently carried out by public administration (PA) employees and labor processes underpinning PA services.

The paper outlines a new framework to estimate the potential impact of DX on the public sector. The authors apply this framework to estimate the value of the impact of DX on the Italian PA, defining the latter by the collection of the value of its labor (i.e. PA workforce salaries) and by the collection of the value of its outputs (i.e. public services’ costs).

This study ultimately maps out the magnitude and trends of how likely the PA occupations and services could be substituted in a wider process of DX. To do this, the authors apply their framework to the Italian PA, and they triangulate secondary data collection, from official accounts of the Italian Ministry of Economics and the National Statistical Institute, with methodological antecedents from the UK Office for National Statistics and experts’ insights. Results provide a snapshot on the type and magnitude of PA jobs and services projected to be affected by automation over the next 10 years.

To the best of the authors’ knowledge, this paper provides for the first time an approach to estimate the value of the impact of DX on the public sector in a data-constrained environment – or in the lack of the required primary data. Once applied to the Italian PA, this approach provides a granular map of the automatability of each of the PA occupations and of the PA services. Finally, this paper mentions preliminary insights on potential challenges related to equity in public sector jobs and implications on recruitment processes.

Handloom products often fail to infiltrate the global or mainland market, resulting in small localized markets, limited demand and profitability. Recent times have also witnessed a decline in the weaving population of India. Assam, accounting for a third of all households engaged in the handloom industry in India, has been widely hit by unemployment, migration and demotivation among weavers due to lack of profitability in the sector. This research aims to study the case of Assam as an exemplar to identify the barriers and cognitive biases impacting the sales of such ethnic apparel and propose nudges as interventions to address such concerns.

A conjoint-based experimental study was used to understand and compare the cognitive biases of two study groups: an ethnic group from Assam and a non-ethnic group from various Tier I and Tier II cities of India. The groups were exposed to a variety of ethnic Assamese and ethnic non-Assamese products to understand their value perception using conjoint analysis.

Results indicate a potential lack of cognitive fluency when dealing with Assamese ethnic garments, triggering System II thinking among the non-ethnic (national buyer) group. The underlying cause may be the inability to attribute substitution of the given product for a more familiar product. The results suggest that exposure may lead to priming, which in turn can increase cognitive fluency.

Within the limits of the literature reviewed, designing a conjoint-based experiment and proposing the use of nudge to popularize certain ethnic garments are novel contributions of this study.