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Brand storytelling is an effective marketing tool. However, when choosing whether to tell more or tell less, it remains unclear which of these two narrative styles is most effective. This study aims to examine whether blank-leaving(less) leads to favourable brand attitudes and compares its effects on consumers’ story immersion, to non-blank-leaving(more).

Two experiments were conducted to test the hypotheses. In Study 1, a single-factorial design was used with 252 participants assigned at random to one of two narrative conditions: blank-leaving or non-blank-leaving. Study 2 replicated Study 1 and investigated the moderating role of implicit mindsets.

The results show that a blank-leaving narrative style increases favourable brand attitudes. Consumers present deeper immersion in the brand story that uses blank-leaving, as compared to non-blank-leaving, leading to a more favourable brand attitude. Furthermore, this effect is stronger for individuals with growth mindsets.

Telling the brand story using a blank-leaving narrative style is more effective in catching consumers’ attention than non-blank-leaving. In particular, a blank-leaving narrative is a good approach for targeting consumers who have a growth mindset.

To the best of the authors’ knowledge, this research is the first to investigate and compare the effects of blank-leaving and non-blank-leaving narrative styles on brand attitudes in the context of storytelling marketing.

The purpose of this study is to investigate the impact of big data (BD) analytics capabilities (BDACs) on green supply chain integration (GSCI) and green innovation (GI) in the context of a developing country, Jordan. In addition, the mediating effect of GSCI on the relationship between BDAC and GI is investigated.

Data collection was carried out through a survey with 300 respondents from food and beverages manufacturing firms located in Jordan. Partial least squares-structural equation modeling (PLS-SEM) technique was applied to analyze the collected data. Natural resource-based view (NRBV) theory was the adopted theoretical lens for this study.

The results revealed that BDAC positively and significantly affects both GSCI and GI. In addition, the results demonstrated that GSCI positively and significantly affects GI. Further, it is also found that GSCI positively and significantly mediates the relationship between BDAC and GI.

This study developed a theoretical and empirical model to investigate the relationship between BDAC, GSCI and GI. This study offers new theoretical and managerial contributions that add value to the supply chain (SC) management literature by testing the mediation model in food and beverages manufacturing firms located in Jordan.

Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive manufacturing (EBAM). However, the literature for finding a slim two-level support is rare. The purpose of this paper is to design a lightweight two-level support structure for EBAM.

To efficiently solve the problem, the lightweight design problem is split into two subproblems: finding a slim Level 1 support and a slim Level 2 support. To solve these two subproblems, this paper develops three efficient metaheuristic algorithms, i.e. genetic algorithm (GA), genetic programming (GP) and particle swarm optimization (PSO). They are problem-independent and are powerful in global search. For the first subproblem, considering the path direction is a critical factor influencing the layout of Level 1 support, this paper solves it by splitting the overhang region into a set of subregions, and determining the path direction (vertical or horizontal) in each subregion using GA. For the second subproblem, a hybrid of two metaheuristic algorithms is proposed: the GP manipulates the topologies of the tree support, while the PSO optimizes the position of nodes and the diameter of tree branches. In particular, each chromosome is encoded as a single virtual tree for GP to make it easy to manipulate Crossover and Mutation. Furthermore, a local strategy of geometric search is designed to help the hybrid algorithm reach a better result.

Simulation results show that the proposed method is preferred over the existing method: it saves the materials of the two-level support up to 26.34%, the materials of the Level 1 support up to 6.62% and the materials of the Level 2 support up to 37.93%. The proposed local strategy of geometric search can further improve the hybrid algorithm, saving up to 17.88% of Level 2 support materials.

The proposed approach for sliming Level 1 support requires the overhanging region to be a rectilinear polygon and the path direction in a subregion to be vertical or horizontal. This limitation limits the further material savings of the Level 1 support. In future research, the proposed approach can be extended to handle an arbitrary overhang region, each with several choices of path directions.

The details of how to integrate the proposed algorithm into the open-source program CuraEngine 4.13.0 is presented. This is helpful for the designers and manufacturers to practice on their own 3D printers.

The path planning of the overhang is a critical factor influencing the distribution of supporting points and will thus influence the shape of the support structure. Different from existing approaches that use single path directions, the proposed method optimizes the volume of the support structure by planning hybrid paths of the overhangs.

The aim of this article is to present a model for the orchestration of dynamic capabilities (ODCs) in cleantech companies that aim to obtain competitive advantage in the market.

The authors present herein descriptive research guided by a qualitative multiple case study approach carried out with 12 cleantech companies.

The results have showed that the ODC model is present in the product/process cycle, thus providing new capabilities and generating sustainable competitive advantage through the research categories presented.

This study contributes to the literature on the ODCs through microfoundations based on evidence of companies inserted in technological and intensively dynamic contexts.

This article demonstrates, through the ODC model, the main capabilities and characteristics of the assets of cleantech companies and how the process of renewing competencies to obtain competitive advantage occurs.

The ODC model utilizes technological resources in the product/process cycle. Asset specificity and the capacity for innovation allow cleantech companies to explore regulatory loopholes, making their sustainable model innovative and obtaining competitive advantage through the renewal of entrepreneurial capabilities and competencies.

Co-working spaces bundle all real estate services into a package and leverage shared economy trend to create new opportunities for growth. This sector is anticipated to expand significantly due to changes in mobility and office design driven by the development of remote or hybrid work settings. The current study attempts to identify key motivating factors for users in emerging economies in choosing co-working spaces.

Using analytic hierarchy process (AHP) methodology and the self-determination theory framework, a total of 4 criteria-level factors, along with 13 sub-criteria level factors were identified as key motivators for adapting to co-working spaces.

The study highlights a few factors and their relative importance, which could help firms/organizations to start or offer co-working spaces within emerging economies.

The study contributes to literature by advancing the understanding of key motivators for users of co-working spaces within the ambits of emerging economies. In the process, the authors enlist a few factors vis-à-vis their relative importance, which could help firms/organizations to start or offer co-working spaces within emerging markets.

The existence of the advertising delay effect and its impact on supply chain operations have been demonstrated in the current study. Therefore, this study develops a timely inventory control strategy for the fresh produce supply chain to address the advertising delay effect in the fresh produce supply chain.

This study proposes a game model based on the Nerlove-Arrow time delay differential equation and Pontryagin's maximum principle. Through comparative analyses of the optimal equilibrium strategies, the authors compare the optimal equilibrium strategies, product goodwill and optimal inventory trajectories for suppliers and retailers under secondary replenishment decisions and decentralized decisions.

The authors find that (1) Only when the sales cycle meets certain conditions can the overall profit of the supply chain under the secondary replenishment decision be greater than that under the decentralized decision. As the price markup coefficient increases, the total profit of the supply chain first increases and then decreases. (2) With the increase in the delay time, the replenishment quantity during the initial period gradually decreases. After the delay time elapses, the inventory depletion rate under secondary replenishment decisions is faster than that under decentralized decision-making. (3) Although there is a continuously increasing maximum value of product goodwill with the increase in delay time, it becomes difficult to achieve this value for longer delays.

The authors’ findings provide a theoretical basis for supply chain members of fresh agricultural products to select replenishment and inventory control strategies when adopting different levels of delay in advertising marketing.

Firstly, this paper explains the impact of advertising delay effect on fresh produce supply chain from a dynamic perspective, and secondly, it provides guidance on advertising formulation and inventory replenishment for fresh produce retailers under the influence of advertising delay effect.

For an entrant platform in the on-demand service market, choosing an appropriate employment model is critical. This study explores how the entrant optimally chooses the employment model to achieve better performance and investigates the optimal pricing strategies and wage schemes for both incumbent and entrant platforms.

Based on the Hotelling model, the authors develop a game-theoretic framework to study the incumbent's and entrant's optimal service prices and wage schemes. Moreover, the authors determine the entrant's optimal employment model by comparing the entrant's optimal profits under different market configurations and analytically analyze the impacts of some critical factors on the platforms' decision-making.

This study reveals that the impacts of the unit misfit cost of suppliers or consumers on the pricing strategies and wage schemes vary with different operational efficiencies of platforms. Only when both the service efficiency of contractors and the basic employee benefits are low, entrants should adopt the employee model. Moreover, a lower unit misfit cost of suppliers or consumers makes entrants more likely to choose the contractor model. However, the service efficiency of contractors has nonmonotonic effects on the entrant's decision.

This study focuses on an entrant's decision on the optimal employment model in an on-demand service market, considering the competition between entrants and incumbents on both the supplier and consumer sides, which has not been investigated in the prior literature.

This study aims to investigate how relationship conflict (RC) hinders green customer integration (GCI) and which strategy could be developed to alleviate the negative effect of RC.

The authors use a sample of 206 Chinese firms to examine hypothesized relationships drawing on social exchange theory and buyer-supplier relationship perspective. Methods including exploratory factor analysis and confirmatory factor analysis are used to assess reliability and validity. Hypotheses are tested using hierarchical regression analysis. Post hoc analysis is adopted to evaluate the robustness.

The results show that RC negatively relates to GCI. Normative commitment partially mediates the relationship between RC and GCI, while the mediating role of instrumental commitment is insignificant. In addition, coercive influence strategy positively moderates the RC-normative commitment and RC-GCI relationships.

While this study clarifies the mechanism of how RC impedes GCI and how to address RC in buyer-supplier relationships, it could be more meaningful to extend the current research and figure out how to address RC in different supply chain relationships. Besides, it will make sense to conduct longitudinal studies and explore the dynamic nature of RC in supply chain relationships.

In practice, firms find it challenging to achieve GCI owing to the ubiquitous existence of RC. The findings reveal that RC detriments GCI partially through normative commitment, and the use of coercive influence strategy mitigates the detriments of RC. Thus, the authors provide solutions for firms to address RC for achieving GCI.

RC is unavoidable in organizational interactions. Prior studies have not revealed the processes through which RC relates to GCI. The authors bridge the gap by exploring the mediating role of organizational commitment and the moderating role of influence strategy, which offers a better understanding of how RC is associated with GCI, and add knowledge of addressing RC for achieving GCI.

This study aims to explore how relationship trust and different types of influence strategy (i.e., non-coercive and coercive influence strategy) impact green customer integration (GCI), while investigating the moderating mechanisms of big data development and social capital.

Following hierarchical linear regression analysis, the authors examine hypothesized relationships by combining survey data from 206 Chinese manufacturers with secondary data.

The results show that relationship trust positively affects non-coercive influence strategy, while its impact on coercive influence strategy is insignificant. Non-coercive influence strategy has an inverted U-shaped impact on GCI. Furthermore, big data development flattens the inverted U-shaped relationship between non-coercive influence strategy and GCI. Conversely, social capital steepens the inverted U-shaped relationship between non-coercive influence strategy and GCI.

This study sheds light on managers on how to involve customers in GCI through friendly strategies that favor the involvement of customers and the willingness to develop environmentally friendly initiatives.

Although GCI has received widespread attention, how it can be enhanced remains unclear. These findings provide novel insights into the emerging GCI literature and complement social exchange theory.

Drawing upon social capital theory, this research aims to explore the influence of three dimensions of green intellectual capital (GIC) (i.e. green human capital [GHC], green structural capital and green relational capital) on green supply chain integration (GSCI) (i.e. green supplier, internal and customer integration), and the mediating effect of supply chain transformational leadership (SCTL).

To verify the hypothesized relationships, the authors conduct hierarchical regression analysis and bootstrapping method with two-waved survey data collected from 317 Chinese manufacturing firms.

The findings suggest that both green structural and relational capital positively influence three dimensions of GSCI, while GHC only positively affects green internal and customer integration. In addition, SCTL mediates the impacts of green structural and relational capital on three dimensions of GSCI and mediates the impacts of GHC on green supplier and internal integration.

This research contributes to the GSCI literature and practice by deeming GIC as an intangible resource that can enhance GSCI and revealing the mediating role of SCTL.