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This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

The development of prefabrication into full-scale offsite manufacturing processes in the construction industry is paradigm-shifting. Moreover, Building Information Modelling (BIM) is becoming the primary mode of communication and integration in construction projects to facilitate the flow of information. Although research has been performed on BIM and Offsite Construction (OSC), integrating these two concepts remains ambiguous and complex and lacks documentation and structure, especially in New Zealand. Therefore, this paper develops a robust framework for OSC and BIM integration. The study focusses on identifying integration challenges and proposes strategies for overcoming these challenges.

This study applied scientometric analysis, a systematic literature review (SLR) and semi-structured expert interviews to investigate OSC and BIM integration challenges. Multiple themes were investigated and triangulation conducted in this research supports the creation of applicable knowledge in this field.

Multiple gaps, research trends and the pioneer countries in the paper's scope have been identified through scientometric analysis. Then, a classified cluster of challenges for OSC and BIM implementation and integration strategies of OSC and BIM were demonstrated from the findings. The interviews provided comprehensive and complementary data sets and analyses. The findings from the Systematic Literature Review and interview structured the integration framework.

The contribution of this paper to existing knowledge is a developed framework that serves as a guideline for the OSC stakeholders. This framework can assess OSC's alignment with BIM and consolidate strategies for incorporating OSC into a BIM-based project delivery process. The framework consists of 23 strategies categorised into 8 clusters: a policy document, training and professional development, documentation, technology management, governmental development, contract development, accurate definition and detailing and communication. The proposed strategies will streamline integration by reducing potential challenges, thus enhancing project productivity.

This paper aims to develop a multi-objective problem for scheduling the operations of trucks entering and exiting cross-docks where the number of unloaded or loaded products by trucks is fuzzy logistic. The first objective function minimizes the maximum time to receive the products. The second objective function minimizes the emission cost of trucks. Finally, the third objective function minimizes the number of trucks assigned to the entrance and exit doors.

Two steps are implemented to validate and modify the proposed model. In the first step, two random numerical examples in small dimensions were solved by GAMS software with min-max objective function as well as genetic algorithms (GA) and particle swarm optimization. In the second step, due to the increasing dimensions of the problem and computational complexity, the problem in question is part of the NP-Hard problem, and therefore multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment.

Therefore, non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA) are used to solve 30 random problems in high dimensions. Then, the algorithms were ranked using the TOPSIS method for each problem according to the results obtained from the evaluation criteria. The analysis of the results confirms the applicability of the proposed model and solution methods.

This paper proposes mathematical model of truck scheduling for a real problem, including cross-docks that play an essential role in supply chains, as they could reduce order delivery time, inventory holding costs and shipping costs. To solve the proposed multi-objective mathematical model, as the problem is NP-hard, multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment. Therefore, NSGA-II and NRGA are used to solve 30 random problems in high dimensions.

This study investigates the impact of government and economic policy uncertainty (EPU) on companies' business operations, especially risk-taking tendencies and corporate financial reporting quality (FRQ).

The study employs the generalised least squares regression model. The final sample comprised 27,376 company-year observations from eight countries in the Asia-Pacific region.

EPU has a negative and significant effect on investment activity and FRQ. Higher EPU leads to a decline in investment and FRQ.

There are several limitations in this study. First, the authors used abnormal investments to measure investments, without considering the degree of irreversibility investment objectives. Second, although control variables are included at the company and country levels, they may only partially control for companies' mitigation effects. Third, the sample is limited to developing countries with unique characteristics in Asia-Pacific; therefore, the findings cannot be generalised.

The findings can help investors, analysts and regulators evaluate EPU's impact on companies' business activities by offering an overview regarding the decline in investment efficiency and FRQ. The results can also be used as input for regulators in formulating policies that encourage companies to regulate investment levels without harming other stakeholders and maintain FRQ during periods of uncertainty.

This research provides intriguing insights into EPU's effects on companies' investment activity and FRQ in developing countries, which are sensitive to changes in macroeconomic conditions.

This study aims to explore a new restaurant category’s development from birth to maturity, thereby explaining the rationale for category innovation strategies.

The authors conducted a qualitative case study analysis of the New Chinese-style Fusion Restaurant category’s development from birth to maturity. Thematic analysis was conducted on data collected from semi-structured interviews and textual information.

A new restaurant category’s maturation is determined by the formation of society’s shared knowledge about the category’s crucial attributes, which is an outcome of market participants’ category-related social practices. The authors develop a novel, four-stage framework for the socialized construction of this shared knowledge: a knowledge creation (KC), knowledge diffusion (KD), knowledge integration (KI) and knowledge structuralization (KS). This knowledge evolution along this KC–KD–KI–KS sequence can holistically describe the category maturation process. This framework can help understand the rationale for a restaurant category’s maturation by analyzing the interrelationships among market participants’ social practices, knowledge-related activities and market development.

This study explains how market participants’ knowledge-related activities facilitate a new restaurant category’s maturation. This can help restaurant managers cope with increasingly homogeneous competition by applying a category-innovation strategy.

This study extends product categorization research on restaurants by articulating a product category’s maturation process from a knowledge perspective.

The development of ‘smart destinations’ has fundamentally altered the travel and tourism sector by making trips more individualised and enhancing overall operational effectiveness. Using (AI) technology in the creation of smart destinations has provided the tourism industry with the opportunity to reimagine and redevelop tourism in a way that is both environmentally responsible and technologically advanced. This chapter investigates the use of AI and smart destinations in China and Hong Kong with the goals of enhancing tourist experiences, boosting environmental sustainability, and propelling economic expansion. AI and smart destinations have greatly impacted China and Hong Kong tourism. AI has improved tourism, customer service, and trip recommendations while intelligent destinations reduce carbon emissions and promote ecotourism to sustain tourism. AI and intelligent locations boost visitor satisfaction and economic growth. As the tourism industry faces future challenges, AI technology and smart destinations will be crucial to creatively and sustainably rebuild tourism. Smart locations and AI have transformed tourism by offering customised, efficient, and environmentally responsible travel experiences.

Risk response decisions (RRDs) are vital for project risk mitigation. Although past research has focused on RRDs for independent single projects, it has scarcely explored how to make RRDs for single projects in project portfolios (SPPPs). Consequently, this study aims to bridge the gap in extant literature by developing an integrated approach to select risk response strategies (RRSs) for SPPPs considering objective adjustments and project interdependencies (PIs).

An integrated quality function deployment (QFD) method was used throughout this study. More so, a balanced score card (BSC) and stratified-Z-numbers-full consistency method (SZFUCOM) was applied to identify SPPP success criteria (SP3SC) to determine their weights. In addition, a spherical fuzzy set-design structure matrix (SFDSM) was used to quantify the correlation between the risks and the relationship between the risks and the predecessor projects. Consequently, the relationships between the risks and SP3SC and RRSs were described by the spherical fuzzy set (SFS) and Z-numbers, respectively. Besides, the results are weaved into QFD to transform SP3SC into risks and then into RRSs, while a linear optimization model is used to obtain the optimal RRSs. Lastly, a construction project portfolio (PP) was used to test the veracity of the results to prove their validity.

The approach to RRDs for single projects is observed to be different from that of SPPPs. In addition, this study finds that project portfolio objective adjustments (PPOAs) and PIs have significant impacts on RRDs given that they influence the risk priorities of independent single projects and SPPPs. Moreover, the application of an integrated QFD effectively synthesized the results from the findings of this study, as well as enabled companies to determine robust RRSs. Finally, the consistency results of the SZFUCOM were better than those of the triangular fuzzy number-full consistency method.

The study innovatively explores the method of RRDs for SPPP, which has been ignored by past research. SP3SC highly compatible with PP success is determined. Z-numbers are first used to evaluate the effect of RRSs to enhance the robustness of RRDs. The study proposes a method of RRDs comprehensively considering PPOAs and PIs, which provides robust methodological guidance for SPPP managers to control risks.

This study aims to focus on exploring the role of fear of missing out (FOMO) in the technology adoption context, whereby the bottom-of-the-pyramid (BOP) segment was studied to explore the factors responsible for the development of behavioural intentions (BI) to use unified payments interface (UPI), a disruptive technological phenomenon in the mobile payment systems field.

A mixed-method research approach involving both qualitative and quantitative methods was used. Initially, qualitative data obtained through interviews with UPI’s BOP users were subjected to thematic analysis, leading to the identification of eight factors and the construction of a conceptual model. Subsequently, 354 responses were gathered, and empirical analysis was conducted using structural equation modelling in AMOS 23.0.

Eight factors, including personal and social benefits, perceived security risk, socio-cultural influences, governmental influence, usability, psychological inertia, perceived value (PV) and FOMO, were discovered. The quantitative examination confirmed the validity of the conceptual model in the BOP context, explaining 51% of the variance in BI. FOMO and PV emerged as robust indicators of UPI adoption, with PV significantly regulating the impact of FOMO.

To the best of the author’s knowledge, this study is one of the first to explore what drives BOP users in an emerging economy to adopt UPI. The conceptual model it presents contributes to the advancement of technology adoption literature by incorporating FOMO alongside newly identified BOP-specific factors.

This study aims to propose an optimization framework using deep neural networks (DNN) coupled with nondominated sorting genetic algorithm II and technique for order preference by similarity to an ideal solution method to improve the tribological properties of camshaft bearing pairs of internal combustion engine.

A lubrication model based on the theory of elastohydrodynamic lubrication and flexible multibody dynamics was developed for a V6 diesel engine. Setting DNN model as fitness function, the multi-objective optimization genetic algorithm and decision-making method were used to optimize the bearing pair structure with the goal of minimizing the total friction loss and the difference of the average values of minimum oil film thickness.

The results show that the lubrication state corresponding to the optimized bearing pair structure is elastohydrodynamic lubrication. Compared with the original structure, the optimized structure significantly reduces the total friction loss.

The optimized performance and corresponding structural parameters are obtained, and the optimization results were verified through multibody dynamics simulation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0417/

Free gifts have become a commonly used marketing strategy. Nevertheless, whether free gifts can and how this strategy promotes the surplus food purchase intention remain a debated topic. This paper attempts to evaluate the effectiveness of offering free gifts (target and non-target products) in enhancing the purchase intention associated with surplus food.

Categorically, Studies 1 to 4 were performed to analyze the impact of the free gift on the surplus food purchase intention, explore the mediating role of perceived quality uncertainty and examine the moderating role of blind-box design and mental simulation.

The study findings indicate that the provision of non-target products as a free gift exerts a more pronounced influence on surplus food purchase intention as compared to offering a target product as a free gift. Evidently, perceived quality uncertainty serves as a mediating role, whereas blind-box design and mental simulation are identified as moderators in this process.

This paper compares the influences of various types of free gifts, namely target and non-target products, on surplus food purchase intention through perceived quality uncertainty, thereby enhancing the existing comprehension of free gifts and surplus food purchase intention. In addition, this article extends the boundary conditions of free gifts by investigating the moderating influence of blind-box design and mental simulation.