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To meet the requirement of establishing an effective schedule for the assembly process with overall detection and rework, this paper aims to address a new problem named resource-constrained multi-project scheduling problem based on detection and rework (RCMPSP-DR).

First, to satisfy both online and offline scheduling, a mixed integer programming model is established with a weighted bi-objective minimizing the expected makespan and the solution robustness. Second, an algorithm that combines a tabu search framework with a critical chain-based baseline generation scheme is designed. The tabu search framework focuses on searching for a reasonable resource flow representing the execution sequence of activities, while the critical chain-based baseline generation scheme establishes a buffered baseline schedule by estimating the tradeoff between two aspects of bi-objective.

The proposed algorithm can get solutions with gaps from −4.45% to 2.33% when compared with those obtained by the commercial MIP solver CPLEX. Moreover, the algorithm outperforms four other algorithms in terms of both objective performance and stability over instances with different weighting parameters, which reveals its effectiveness.

The represented RCMPSP-DR considering the overall detection and rework is an extension of the scheduling problem for large-scale equipment. An effective algorithm is proposed to establish the baseline schedule and determine the execution sequence of activities for the assembly process, which is significant for practical engineering applications.

In response to the station design and flexible resources allocation of the aircraft moving assembly line, a new problem named flexible resource investment problem based on project splitting (FRIP_PS), which minimizes total cost of resources with a given deadline are proposed in this paper.

First, a corresponding mathematical model considering project splitting is constructed, which needs to be simultaneously determined together with job scheduling to acquire the optimized project scheduling scheme and resource configurations. Then, an integrated nested optimization algorithm including project splitting policy and job scheduling policy is designed in this paper. In the first stage of the algorithm, a heuristic algorithm designed to get the project splitting scheme and then in the second stage a genetic algorithm with local prospective scheduling strategy is adopted to solve the flexible resource investment problem.

The heuristic algorithm of project splitting gets better project splitting results through the job shift selection strategy and meanwhile guides the algorithm of the second stage. Furthermore, the genetic algorithm solves resources allocation and job schedule through evaluation rules which can effectively solve the delayed execution of jobs because of improper allocation of flexible resources.

This paper represents a new extension of the resource investment problem based on aircraft moving assembly line. An effective integrated nested optimization algorithm is proposed to specify station splitting scheme, job scheduling scheme and resources allocation in the assembly lines, which is significant for practical engineering applications.

Both the scope of postentry growth and the scale of postentry growth are essential for Chinese multinational enterprises' aggressive internationalization. Yet, prior literature has not considered the synergistic approach of postentry growth that seeks the scope of growth and the scale of growth simultaneously. Building upon the embeddedness perspective and the learning view, we address how structural embeddedness directly affects firms' postentry growth in the form of scope and scale and indirectly affects postentry growth via both the scope of growth and the scale of growth. Particularly, we investigate the decreasing mediating effect of the growth's scale on the growth's scope when embeddedness strengthens.

With a survey data set of 206 Chinese multinational firms from manufacturing and service industries, we conduct structural equation modeling (SEM), partial least squares path modeling (PLS-PM), instantaneous indirect effect assessment and hierarchical linear regression model to test our hypotheses.

First, Chinese multinational enterprises’ (CMNEs) structural embeddedness is positively related to their scope of postentry growth, while has a U-shaped relationship with their scale of postentry growth. Second, CMNEs' scope of postentry growth mediates the relationship between structural embeddedness and the scale of postentry growth, the mediation effect counts for 33.5% of the over effect. Finally, the indirect effect of structural embeddedness on the scope of postentry growth through the scale of postentry growth is nonlinear. As the structural embeddedness strengthens, the positive indirect effect gradually weakens.

We believe this study further connects core international business research on postentry growth to the fast-growing literature on emerging markets multinational enterprises' internationalization. In addition, we undertake an initial effort in addressing an important gap in the literature: how structural embeddedness matters to firms' postentry growth. Moreover, this study finds important evidence to support the direct and indirect effect of structural embeddedness on postentry growth.

This study aims to examine the determinants of adoption intention toward the rooftop solar photovoltaic (RSPV) systems among residents of peri-urban villages of Gurugram, Haryana, India. This study also analyzes the impact of the adoption of RSPV systems on carbon neutrality from a behavioral perspective.

Data was collected using a self-administrated structured questionnaire from 208 male villagers (195 usable) of 22 villages using the purposive sampling technique.

Results revealed that relative advantage, followed by simplicity, trialability, observability and compatibility, positively and significantly impact villagers’ attitude toward adopting RSPV systems in their homes. Perceived severity and perceived vulnerability significantly influence the perceived behavioral control of villagers toward adopting the RSPV systems. The results show villagers’ attitudes, subjective norms and perceived behavioral control are the essential predictors of their adoption intention of the RSPV systems. Most notably, carbon neutrality was significantly affected by villagers’ adoption intention of RSPV systems as the renewable energy source in their homes.

The findings of this study provide that innovation attributes are important factors in shaping the adoption intentions of customers toward RSPV systems. This study is also the extent of previous studies measuring customers’ perception of adopting renewable energy in developed and emerging countries worldwide.

Emerging technologies have the capacity to transform industries offering substantial benefits to users. Given the increasing demand for advanced logistics services, third-party logistic service providers (LSPs) face greater pressure to deploy and realise these technologies, especially given the demands and operational challenges created during the COVID-19 crisis. Drawing upon the diffusion of innovation (DOI) theory and technology–organisation–environment (TOE) framework, this paper goes beyond just identifying drivers and barriers to technology adoption to understanding how LSPs and industry experts perceive these drivers and barriers and simultaneously confront and undertake actions to implement them.

An exploratory study was conducted in three phases: (1) in-depth interviews with twelve stakeholders in the Australian logistics industry; (2) five in-depth interviews conducted with stakeholders during the COVID-19 crisis and (3) a focus group discussion session. All interviews were analysed using content analysis and revealed several drivers for the deployment of emerging technologies, including internal organisational factors that drive supply chain (SC) network optimisation.

The analysis of the three phases identified several drivers for the deployment of emerging technologies in logistics, including internal organisational factors that drive SC network optimisation. Also identified were external drivers including the impact of the COVID-19 crisis, along with barriers and specific actions that were considered and implemented by LSPs for sustainable operations, particularly in a post-COVID-19 environment.

This study explores organisational and industry drivers for the implementation of emerging technologies. Explicitly, it extends the extant research by highlighting organisational and industry drivers and enablers that influence adoption and deployment of emerging technologies. Second, it advances the existing perspectives on LSPs in the Australian context on the development and implementation of technology strategies. The paper offers insights around implementation of technologies, directly obtained from industrial application for managers and practitioners.