Search results

Three-dimensional (3D) food printing is an innovative technology used to customize food products through the integration of digital technology and food ingredients. The purpose of this study is to assess the current state of research in the field of 3D food printing, identify trending topics and identify promising future research directions.

This bibliometric review systematically evaluates the field of 3D food printing using data from published literature in the Web of Science database. After reference screening, 812 articles were included in the analysis.

The result reveals that research in 3D food printing primarily focuses on the optimization and characterization of mechanical and rheological properties of food inks and that post-printing processing, such as laser treatment, has emerged recently as an important consideration in 3D food printing. However, extant works lack animal and human studies that demonstrate the functionality of 3D-printed food.

This sophisticated bibliometric analysis uncovered the most studied current research topics and the leading figures in the area of 3D food printing, providing promising future research directions.

The purpose of this study is to present a system dynamic (SD)-based remanufacturing economic analysis model of used automobile engine under two recycling modes. The authors will compare the remanufacturing cost, sales profit and sales revenue from time and space dimensions incurred in different recycling modes in the long run.

The remanufacturing economic analysis model is based on SD methodology. The authors can simulate the relations of impact factors on automobile engine recycling and remanufacturing and further analyze and compare the cost, sales profit and sales revenue incurred in different recycling modes in the long term.

Sinotruk Steyr engine remanufacturing in Shandong province is taken as the research case subject. The revenue, cost and profit under the two recycling modes from 2015 to 2035 are analyzed and compared. The results show that different recycling modes have significant varying influence on the economy of engine remanufacturing.

This economic analysis model can provide a method reference to decide the recycling mode for auto components and other product remanufacturing. Moreover, this model can guide and support the sustainable development of remanufacturing industry.

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.

This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF.

This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method.

The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism.

This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners.

The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.

This study aims to explore the spatial impact of an increase in the minimum wage on the labor productivity of star-rated hotels in China.

The impact is analyzed by using the dynamic spatial Durbin model.

The authors find a U-shaped link between the increase in minimum wage and labor productivity of star-rated hotels. The long-term impact of a minimum wage increase has a greater influence on labor productivity than its short-term effects. While there is no notable spatial spillover impact observed in the sample of 31 provinces in China, the authors do identify a spatial spillover effect of the minimum wage rises on the labor productivity of star-rated hotels in the central area. Furthermore, they observe heterogeneity across China. The eastern and western regions exhibit a U-shaped relationship, whereas the central region exhibits an inverted U-shaped relationship.

The findings of this study allow government agencies to get a more comprehensive comprehension of the actual consequences of minimum wage hikes on the tourism and hospitality sector, thereby establishing a solid basis for them to develop appropriate policies. Moreover, it offers a variety of suggestions aimed at enhancing the quality and efficiency of hotel management.

Research on the effects of minimum wage standards is scant in the hospitality industry. Based on human capital investment theory, this study examines the effect of the minimum wage standard hikes on labor productivity of star-rated hotels from the spatial perspective, filling the existing research gap.

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into electronic word-of-mouth management for the industry.

This study elaborates a hybrid model that integrates deep learning (DL) and a sentiment lexicon (SL) and compares it to five other models, including SL, random forest (RF), naïve Bayes, support vector machine (SVM) and a DL model, for the task of emotion recognition in restaurant online reviews. These models are trained and tested using 652,348 online reviews from 548 restaurants.

The hybrid approach performs well for valence-based emotion and discrete emotion recognition and is highly applicable for mining online reviews in a restaurant setting. The performances of SL and RF are inferior when it comes to recognizing discrete emotions. The DL method and SVM can perform satisfactorily in the valence-based emotion recognition.

These findings provide methodological and theoretical implications; thus, they advance the current state of knowledge on emotion recognition in restaurant online reviews. The results also provide practical insights into intelligent service quality monitoring and electronic word-of-mouth management for the industry.

This study proposes a superior model for emotion recognition in restaurant online reviews. The methodological framework and steps are elucidated in detail for future research and practical application. This study also details the performances of other commonly used models to support the selection of methods in research and practical applications.

The purpose of this paper is to investigate the impact of demand information sharing on products’ greening levels with downstream competition. Specifically, this study examine two types of green products, “development-intensive” (DI) and “marginal-cost intensive” (MI), in a two-echelon supply chain where the manufacturer produces substitutable products, and competing retailers operate in a market with uncertain demand.

The authors adopt the manufacturer-led Stackelberg game-theoretic framework and consider a multistage game. This study consider how retailers receive private signals about uncertain demand and decide whether to share this information with the manufacturer, who then decides whether to acquire this information at a certain given cost. This paper considers backward induction and Bayesian Nash equilibrium to solve the model.

The authors find that in the absence of competition, information sharing is the only equilibrium and improves the greening level under DI, whereas no-information sharing is the only equilibrium and improves the greening level under MI, an increase in downstream competition drives higher investment in greening efforts by the manufacturer in both DI and MI and the manufacturer needs to offer a payment to the retailers to obtain demand information under both simultaneous and sequential contract schemes.

This paper contributes to the literature by examining how the nature of products (margin intensive green product or development intensive green product) influences green supply chain decisions under information asymmetry and downstream competition.

This study investigates near field communication (NFC) payment method adoption in the Republic of Kosova, aiming to understand factors influencing consumer behavior toward NFC technology adoption. Using the Unified Theory of Acceptance and Use of Technology (UTAUT-3) model and perceived risk theory, the research seeks to establish relationships between various factors and user intentions regarding NFC payment technology.

Using a quantitative approach, the research used a comprehensive questionnaire of 40 questions rated on a seven-point Likert scale across 16 constructs aligned with the research objectives. A convenience sampling method was used, distributing electronic questionnaires to 200 individuals representing diverse demographics in the Republic of Kosova.

The study identified significant support for numerous hypotheses, demonstrating substantial correlations between factors like performance expectancy, effort expectancy, social influence, habit, facilitating conditions and personal innovativeness with behavioral intention to use and behavioral intention to adopt NFC payments.

Because convenience sampling was used, there are restrictions on the study’s sample size. Moreover, although the study delves into noteworthy elements impacting the adoption of NFC payment systems, it might not cover all possible factors that could influence consumer behavior in this regard.

Policymakers, NFC product developers, companies in the technology and payment sectors and Republic of Kosova customers all gain strategically from the research’s findings. Policymakers may make informed judgments about legislation, improve product development and marketing tactics and empower consumers to accept NFC payments by having a better understanding of consumer preferences and behaviors related NFC technology.

Understanding consumer preferences and behaviors regarding NFC technology can refine product development and marketing strategies, inform policymaking and empower consumers’ decisions about adopting NFC payments.

This study’s innovative approach in combining the UTAUT-3 model and perceived risk theory contributes significantly to the understanding of factors influencing users’ intentions in adopting emerging payment technologies, filling a gap in NFC payment literature.

This study aims to examine the effect of marketing agility of startup companies on their new product creativity and new product performance while examining the moderating role of technological turbulence.

Data were collected from 319 South Korean startups and empirically analyzed using structural equations modeling technique.

First, marketing agility is a potent catalyst that positively influences the novelty and meaningfulness of new products, thereby enhancing new product creativity. Second, marketing agility contributes significantly to new product performance across multiple dimensions, including market, financial, and customer performances. Third, this study underscores the pivotal role of new product creativity, with both novelty and meaningfulness proving to be key drivers of improved new product performance. Technological turbulence is revealed as a moderating force, amplifying the positive relationship between new product novelty and performance. However, while it substantiates some moderating effects, the study does not find significant support for the role of technological turbulence in moderating the relationships among new product meaningfulness, marketing agility, and new product performance.

To the best of our knowledge, this study is the first to analyze the effect of startups’ marketing agility on new product creativity and performance considering the moderating effect of technological turbulence, especially in the South Korean context. This study offers practical insights emphasizing the indispensability of marketing agility for startups operating in rapidly evolving markets. Additionally, it advocates a strategic emphasis on novelty in high-tech turbulence scenarios to bolster new product performance.

This study aims to identify the intermediate psychological mechanism – organizational identification – that links authentic leadership with follower’s organizational citizenship behavior (OCB). Moreover, it examines the moderating role of perceived organizational support (POS) in the relationship between authentic leadership and organizational identification.

This study uses a cross-sectional research design involving 356 employees from diverse corporations in South Korea. Data were collected using a structured questionnaire to measure perception of authentic leadership, organizational identification, POS and OCB.

The results indicate that organizational identification significantly mediates the relationship between the perception of authentic leadership and follower’s OCB. Furthermore, POS acts as a moderating variable, strengthening the relationship between authentic leadership and organizational identification. Specifically, followers who perceive strong support from their organization are more likely to develop a robust sense of organizational identification under authentic leadership, which in turn, enhances their OCB.

This study offers a novel integration of social identity theory and organizational support theory to examine how authentic leadership influences follower’s OCB. It is among the first to introduce organizational identification as an intermediary in this context and to investigate the moderating effect of POS. The findings provide valuable insights for managers aiming to cultivate a workplace culture that fosters organizational identification and citizenship behaviors, thereby enhancing organizational effectiveness. Future research directions are also highlighted.