Search results

Firms are subject to power from both upstream and downstream partners; those partners may have different or even opposing impacts on supply chain relationships and financial performance. The purpose of this study is to investigate how upstream and downstream dependence structures affect a firm's financial performance through upstream and downstream relational depth (DEP) and relationship extendedness (EXT).

Data representing both upstream and downstream supply chain perspectives was collected using a multiple-respondent survey and was further augmented using financial performance data from an archival database.

Dependence advantages (ADVs) and disadvantages from upstream and downstream partners affect relational mechanisms and firm performance differently. Only downstream ADV will enhance a firm's DEP and EXT and subsequently affect firm's revenue and profit. Contradictory to widely held belief, the results reveal that firms that maintain long-term relationships with buyers and suppliers may experience lower revenue/profit.

This research represents a significant step in understanding the economic ramifications of dependence by (1) highlighting the difference between upstream and downstream supply chain dependence structure and (2) understanding the indirect effects of dependence structure on financial performance.

Using perspectives from the technology affordance and social capital theories, this study aims to unpack the process through which platform-enabled co-development unfolds in supply chain contexts. Specifically, it explores how innovation outcomes can be fostered through platform affordances and supply chain relationship (SCR) capital.

The paper integrates literature on digital platforms, SCRs and co-development to produce an integrative framework, developing propositions on the relationships among digital platforms, SCR capital and innovation outcomes.

The authors identify affordances for distinctive strategic use of platforms: value co-creation, relationship building and strategic learning. The authors discuss ways in which each affordance contributes to the advances in SCR capital, thus altogether enabling focal firms to orchestrate and integrate internal and external resources to attain incremental and radical innovation.

Based on the proposed research framework, further empirical studies can use quantitative data to measure the relationship between affordances and SCR capital and use longitudinal case studies to explore how affordances and SCR capital evolve to provide more fine-grained and contextualised information in different research settings.

This paper sheds light on how the relation between the adoption of digital platforms and SCR capital shapes digitally enabled service co-development. The authors provide an alternative explanation of resource integration in platform-mediated supply chain contexts and enrich the related literature on how digital platforms can maximise value from introducing ambidextrous innovation by leveraging internal and external resources.

This study aims to examine whether customer trust is influenced by the congruence and incongruence between customers' perceptions of two types of omnichannel integration—perceived transactional integration (PTI) and perceived relational integration (PRI). The authors further considered the perceived effectiveness of e-commerce institutional mechanisms (PEEIM) as the boundary condition of omnichannel integration's effect.

Drawing upon the stereotype content model, this study hypothesizes the influences of PTI and PRI on customer trust wherein PEEIM moderates the relationships. The research model was empirically examined based on the responses surface analysis of survey data collected from 311 omnichannel customers.

Results showed that when PTI and PRI are congruent, customers are inclined to trust brands that have high levels of PTI and PRI rather than low levels of PTI and PRI. Moreover, the incongruence between PTI and PRI is positively related to customer trust. PEEIM was found to weaken the congruence effect while strengthening the incongruence effect. The authors also examined customer distrust as another relational outcome to provide a robust check.

This study uncovers customer cognition of omnichannel integration and examines the influences on customer trust, therefore contributing to our understanding of omnichannel integration's effect from the customer perspective. Findings from this research provide insights for brand managers on deploying channel integration strategies and institutional mechanisms to manage customer trust.

This method will become a new development trend in subgrade structure design for high speed railways.

This paper summarizes the structural types and design methods of subgrade bed for high speed railways in China, Japan, France, Germany, the United States and other countries based on the study and analysis of existing literature and combined with the research results and practices of high speed railway subgrade engineering at home and abroad.

It is found that in foreign countries, the layered reinforced structure is generally adopted for the subgrade bed of high speed railways, and the unified double-layer or multi-layer structure is adopted for the surface layer of subgrade bed, while the simple structure is adopted in China; in foreign countries, different inspection parameters are adopted to evaluate the compaction state of fillers according to their respective understanding and practice, while in China, compaction coefficient, subsoil coefficient and dynamic deformation modulus are adopted for such evaluation; in foreign countries, the subgrade top deformation control method, the subgrade bottom deformation control method, the subsurface fill strength control method are mainly adopted in subgrade bed structure design of high speed railways, while in China, dynamic deformation control of subgrade surface and dynamic strain control of subgrade bed bottom layer is adopted in the design. However, the cumulative deformation of subgrade caused by train cyclic vibration load is not considered in the existing design methods.

This paper introduces a new subgrade structure design method based on whole-process dynamics analysis that meets subgrade functional requirements and is established on the basis of the existing research at home and abroad on prediction methods for cumulative deformation of subgrade soil.

Frequently the universities' Placement Service is based on the student's hard profile at the expense of soft traits. On the other side, the “person–organization fit” axiom suggests firms are looking for profiles with specific soft skills to face the increasing level of environmental turbulence. This research aims to understand if high-resilience students also have high academic achievements and how the three components of resilience (emotional intelligence, positive thinking, planfulness) can have different impact on individual performances.

The research was conducted on students enrolled on different courses of studies and years in an Economics and Law faculty. A questionnaire was administered during the first exam session (ante-Covid) and the second and third exam sessions (post-Covid). This questionnaire consists of 84 questions related to planfulness, emotional intelligence and positive thinking, whose combination can be considered a measure of resilience. In fact, the Principal Component Analysis (PCA) was carried to identify these three new variables (the components) based on the 84 initial ones. Finally, an ordered logit model was implemented to verify whether, and in what direction, planfulness, emotional intelligence, positive thinking and Covid 19 (the independent variables) affected the students' performance (the dependent one).

While planfulness positively affected academic performance, emotional intelligence affected it negatively. The impact of positive thinking and Covid was not significant, and thus what emerged from the preliminary analysis of the grades is not confirmed.

This is a case study of a university experience that is paying great care in preparing students to satisfy the firms' work demands. To confirm and refine results the sample will be expanded to other faculties and other life/soft skills will be investigated.

This soft trait approach—that studies how various measures of soft skills are related to course grades—has a two-fold significance by crafting universities' placement activities and facilitating firms' onboarding.

This is a case study of a university experience; a university that is paying great attention to preparing students ready to satisfy the firms' work demands but also citizens capable of supporting the growth of their nation and society in general.

The research can be considered a first step towards the inclusion of the formal evaluation of the students' life skills in their academic path, creating a link with their achievements.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

The purpose of this paper is to examine the effect of subjective ambivalence on ethical consumption behaviors and the role of ethical claims in reducing feelings of ambivalence toward buying ethical products.

The authors conducted two studies. In study 1, the authors carried out an online survey with a sample of 230 French consumers. The authors applied structural equation modeling with Amos to test the relationships among skepticism, ambivalence and ethical consumption behaviors. Study 2 is an experimental design in which the authors manipulated ethical claims (low – few ethical arguments vs. high – many ethical arguments) in advertising (176 French panelists). The authors tested the relationships among consumer ethical sensitivity, perceived brand ethicality, skepticism, ambivalence and intention to purchase an ethical product, depending on ethical claims in advertising.

Study 1 shows that skepticism toward advertising of ethical products amplifies feelings of ambivalence and that ambivalence reduces consumers’ willingness to adopt ethical consumption behaviors. Study 2 shows that strong claims in advertising of ethical products reduce skepticism toward advertising of ethical products and feelings of ambivalence toward buying an ethical product through perceived brand ethicality, with consumers’ ethical sensitivity positively moderating these relationships.

The two studies explore only one form of ambivalence (i.e. subjective), and the experimental study focuses on a single category of products.

The findings highlight the difficulties in promoting ethical products. Consumers need to know if a product is “really” ethical, as they may feel ambivalent toward that product. This paper shows that strong ethical claims in advertising ethical products significantly help to overcome this barrier.

Based on attribution theory and persuasion models, this research reveals how ethical claims in advertising affect feelings of ambivalence, which negatively influence consumers’ willingness to adopt ethical consumption. In addition, it follows a holistic approach to ethical consumption behaviors to explore consumers’ ambivalence.

Multi-view fuzzy clustering algorithms are not widely used in image segmentation, and many of these algorithms are lacking in robustness. The purpose of this paper is to investigate a new algorithm that can segment the image better and retain as much detailed information about the image as possible when segmenting noisy images.

The authors present a novel multi-view fuzzy c-means (FCM) clustering algorithm that includes an automatic view-weight learning mechanism. Firstly, this algorithm introduces a view-weight factor that can automatically adjust the weight of different views, thereby allowing each view to obtain the best possible weight. Secondly, the algorithm incorporates a weighted fuzzy factor, which serves to obtain local spatial information and local grayscale information to preserve image details as much as possible. Finally, in order to weaken the effects of noise and outliers in image segmentation, this algorithm employs the kernel distance measure instead of the Euclidean distance.

The authors added different kinds of noise to images and conducted a large number of experimental tests. The results show that the proposed algorithm performs better and is more accurate than previous multi-view fuzzy clustering algorithms in solving the problem of noisy image segmentation.

Most of the existing multi-view clustering algorithms are for multi-view datasets, and the multi-view fuzzy clustering algorithms are unable to eliminate noise points and outliers when dealing with noisy images. The algorithm proposed in this paper has stronger noise immunity and can better preserve the details of the original image.

The purpose of this paper is mainly to know: (1) the sound absorption coefficient of porous composite structures constituted by a new kind of lightweight ceramic foam and perforated plate; (2) the availability of an equivalent porous material model, recently proposed by the present author, to these composite structures in sound absorption.

A kind of lightweight ceramic foam with bulk density of 0.38–0.56 g·cm-3 was produced by means of molding, drying and sintering. The effect of stainless steel perforated plate on sound absorption performance of the ceramic foam was investigated by means of JTZB absorption tester.

The results indicate that the sound absorption performance could be obviously changed by adding the stainless steel perforated plate in front of the porous samples and the air gap in back of the porous samples. Adding the perforated plate to the porous sample with a relatively large pore size, the sound absorption performance could be evidently improved for the composite structure. When the air gap is added to the composite structure, the first absorption peak shifts to the lower frequency, and the sound absorption coefficient could increase in the low frequency range.

Based on the equivalent porous material model and the “perforated plate with air gap” model, the sound absorption performance of the composite structures can be simulated conveniently to a great extent by using Johnson-Champoux-Allard model.

Due to the popularity of mobile devices and the development of artificial intelligence (AI), AI-powered mobile fitness applications (MFAs) have entered people's daily lives. However, the extant literature lacks empirical investigations that explore users' continuance usage intentions regarding AI-powered MFAs. To fill this research gap, this paper employs goal-setting theory to establish a research model for exploring how AI-enabled features (i.e. intelligence and anthropomorphism) affect users' perceptions of goal difficulties and goal specificities, which in turn affect their MFA continuance usage intentions.

This paper uses a survey method to analyze the research model, and a total of 223 responses are collected. The partial least squares (PLS) technique is utilized for data analysis.

The results show that intelligence and anthropomorphism affect the continuance usage intention of MFA users through their goal difficulty and specificity. Both intelligence and anthropomorphism positively influence goal specificity, whereas they negatively affect goal difficulty. In addition, goal specificity increases users' MFA continuance usage intention, whereas goal difficulty decreases users' continuance usage intention. The findings of this study provide theoretical contributions for AI technology adoption research and offer practical strategies for firms to retain MFA users.

Based on goal-setting theory, this study reveals that as two primary AI features of contemporary mobile fitness apps, intelligence and anthropomorphism, can increase comprehension of users' perceptions regarding goal difficulty and specificity in the context of users' continuance usage intentions toward AI-powered MFAs.