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This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

This study explores the intricate relationship between inventory leanness, financial constraints and digital transformation in listed Chinese manufacturing firms.

Using a large panel data collected from 2,563 Chinese listed manufacturing enterprises over the period from 2012 to 2021, this research employs the instrumental variable method combined with two-stage least squares estimators to explore the U- shaped relationship between inventory leanness and financial constraints. Furthermore, the moderating role of digital transformation is demonstrated.

Contrary to traditional assumptions, our research uncovers a U-shaped relationship between inventory leanness and financial constraints, indicating that excessive inventory reduction can exacerbate financial constraints. Digital transformation plays a significant moderating role, particularly in highly digitalized environments.

Our findings have practical significance for top managers and policymakers. We advocate for a balanced approach to lean inventory management to mitigating financial constraints. The study emphasizes the pivotal role of digital transformation in alleviating the impact of inventory leanness on financial constraints, highlighting the need for digital transformation strategies.

This research provides a comprehensive analysis of inventory leanness, financial constraints and digital transformation dynamics. It challenges conventional thinking by revealing the nonlinear nature of the inventory leanness–financial constraints relationship. The concept of moderation highlights the moderating effect of digital transformation. This study offers practical guidance for practitioners and policymakers.

In response to the challenge of reduced efficiency or failure of robot motion planning algorithms when faced with end-effector constraints, this study aims to propose a new constraint method to improve the performance of the sampling-based planner.

In this work, a constraint method (TC method) based on the idea of cross-sampling is proposed. This method uses the tangent space in the workspace to approximate the constrained manifold pattern and projects the entire sampling process into the workspace for constraint correction. This method avoids the need for extensive computational work involving multiple iterations of the Jacobi inverse matrix in the configuration space and retains the sampling properties of the sampling-based algorithm.

Simulation results demonstrate that the performance of the planner when using the TC method under the end-effector constraint surpasses that of other methods. Physical experiments further confirm that the TC-Planner does not cause excessive constraint errors that might lead to task failure. Moreover, field tests conducted on robots underscore the effectiveness of the TC-Planner, and its excellent performance, thereby advancing the autonomy of robots in power-line connection tasks.

This paper proposes a new constraint method combined with the rapid-exploring random trees algorithm to generate collision-free trajectories that satisfy the constraints for a high-dimensional robotic system under end-effector constraints. In a series of simulation and experimental tests, the planner using the TC method under end-effector constraints efficiently performs. Tests on a power distribution live-line operation robot also show that the TC method can greatly aid the robot in completing operation tasks with end-effector constraints. This helps robots to perform tasks with complex end-effector constraints such as grinding and welding more efficiently and autonomously.

This study delves into the nuanced implications of short-sale constraints on stock prices within the context of stock market efficiency. While existing research has explored this relationship, inconsistencies persist in their findings. The purpose of this study is to conduct a comprehensive review of literature to elucidate the reasons behind these disparities.

A systematic review of existing theoretical and empirical studies was conducted following the PRISMA method. The analysis centered on discerning the factors contributing to the divergence in projected stock prices due to these constraints. Key areas explored included assumptions related to expectations homogeneity, revisions, information uncertainty, trading motivations and fluctuations in supply and demand of risky assets.

The review uncovered multifaceted reasons for the disparities in findings regarding the influence of short-sale constraints on stock prices. Variations in assumptions related to market expectations, coupled with fluctuations in perceived information uncertainty and trading motivations, were identified as pivotal factors contributing to differing projections. Empirical evidence disparities stemmed from the use of proxies for short-sale constraints, varied sample periods, market structure nuances, regulatory changes and the presence of option trading.

This study emphasizes the significance of not oversimplifying the impact of short-sale constraints on stock prices. It highlights the need to understand these effects within the broader context of market structure and methodological considerations. By delineating the intricate interplay of factors affecting stock prices under short-sale constraints, this review provides a nuanced perspective, contributing to a more comprehensive understanding in the field.

The purpose of this study is to identify and evaluate the primary constraints that quantity surveying firms in Nigeria encounter while integrating indoor environmental quality (IEQ) principles into building designs.

The study used a quantitative approach by administering a well-structured questionnaire to 114 quantity surveyors. The collected data were analyzed using methods such as frequencies, percentages, mean item scores, Kruskal–Wallis test and exploratory factor analysis.

The top five ranked constraints were limited access to funding or financing options, limited availability of green materials, limited availability of insurance for sustainable buildings, limited availability of sustainable design resources and limited diversity and inclusivity within the design profession. Based on the factor analysis, the study identified six clusters of constraints: structural-related constraints, technical-related constraints, financial-related constraints, capacity-related constraints, legal-related constraints and culture-related constraints.

This study has several practical implications for quantity surveying firms, policymakers and industry stakeholders involved in building design and construction in Nigeria. The findings of this study can also inform future research on the integration of IEQ principles into building designs.

By identifying and structuring the clusters of constraints faced by quantity surveying firms in Nigeria when implementing IEQ principles, this study provides a novel approach to understanding the challenges associated with IEQ implementation in the building sector. This understanding can guide policymakers, industry stakeholders and quantity surveying firms in developing effective strategies to overcome these constraints and promote IEQ principles in building design and construction.

A scheduling method for determining the critical path in linear projects is presented, that takes into account maximum time and distance constraints in addition to the commonly used minimum time and distance constraints. The maximum constraints, though often present in the specifications of a project, are not considered during the planning procedure, since no method existed to enable scheduling with them. The proposed method builds on the concept of the maximum constraints and expands on the necessary background for their implementation into the schedule. The introduced critical path algorithm allows for grouping linear activities into four categories regarding their critical status and their ability to influence project duration. The method is applied to a low‐pressure pipeline construction project and the results are presented.

Product configuration is considered as one of the most successful applications of knowledge‐based approaches in the past decade. Knowledge‐based configurations can be classified into three different approaches, namely, rule‐based, model‐based and case‐based approaches. Past research has mainly focused on the development of reasoning techniques for mapping requirements to configurations. Despite the success of certain conventional approaches, the acquisition of configuration knowledge is usually done manually. This paper aims to explore fundamental issues in product configuration system, and propose a novel approach based on data mining techniques to automatically discover configuration knowledge in constraint‐based configurations.

Given a set of product data comprising product requirements specification and configuration information, the paper adopted an association rule mining algorithm to discover useful patterns between requirement specification and product components, as well as the correlation among product components. A configuration was developed which takes XML‐based requirement specification as input and bases on a constraint knowledge base to produce product configuration as output consisting of a list of selected components and the structure and topology of the product. Three modules are developed, namely product data modelling, configuration knowledge generation and product configuration generation module. The proposed approach is implemented in the configuration knowledge generation module. The configuration generation module realizes a resolution of constraint satisfaction problem to generate the output configuration.

The significance and effectiveness of the proposed approach is demonstrated by its incorporation in our configuration system prototype. A case study was conducted and experimental results show that the approach is promising in finding constraints with given sufficient data.

Novel knowledge generation approach is proposed to assist constraint generation for Constraint‐based product configuration system.

This paper's objective is to explain the concept of proper kinematic constraint to guide requirements‐driven design of mechanical assemblies and to connects proper constraint to the datum flow chain (DFC) and key characteristics (KCs).

The paper presents proper constraint as a way to support the goal of placing key parts in particular geometric relationships with respect to one another so that a DFC can deliver KCs unambiguously. Such a DFC is said to be competent. Additionally, a competent DFC is robust in the sense that the constraint relationships between parts retain their definition and effect under all allowed variations in parts.

Failure to provide proper constraint can lead to undesired consequences including locked‐in stresses and difficult or inconsistent assembly. Some designs need to be over‐constrained, and this requires very careful control and tight tolerances on the over‐constrained degrees of freedom in order to avoid or at least understand the consequences listed above.

Mathematical methods exist to test designs for proper constraint. The simplest, and occasionally unsuccessful, is the Kutzbach criterion. Screw theory is the most reliable method but its application requires extra knowledge and mathematical tools.

Most CAD software and tolerance analysis software do not test designs for their state of constraint. The engineer needs to take account of this independently and be aware of the limitations of software as a guide. Tolerance analysis software that does not take account of constraint may yield incorrect answers.

The paper reinvigorates a once‐well‐known principle and makes engineers aware of it. It also links this concept to the concepts of DFC and KCs and supports a mathematically‐based method for designing assemblies.

The popularity of adventure activities in leisure and tourism is escalating, yet little is known about how personality and perceived constraints can prevent consumption of such activities. The aim of this study was to test a model of the mediating role of psychological constraints in explaining the relationship between personality and interest in adventure activity participation. Based on a questionnaire survey of 1,324 respondents, a quantitative analysis using structural equation modeling (SEM) was carried out. The results show that personality does influence psychological constraints, which in turn have a significant negative effect on adventure activity participation. Increased knowledge about the constraints to adventure activity participation can contribute to realizing the full development potential that lies in adventure consumption in leisure and tourism. Implications of the research can prove valuable in both leisure and tourism marketing and management.

Entrepreneurs and their ventures face innumerous constraints (e.g., lack of funding, lack of business skills, and lack of social support) since the moment business opportunities are identified and chased, until the venture comes to reality. Scholars have conceptualized constraints as obstacles in nature, that is, as always undermining entrepreneurs’ behavior. Nonetheless, prior research has presented conflicting results. Specifically, a same constraint may or may not have a negative effect on entrepreneurs’ action. As advanced by Van Gelderen, Thurik, and Patel (2011), this suggest that “the nature of [entrepreneurial] problems is essentially evaluative, and therefore subjective.” Accordingly, a same constraint may be seen as a problem by one person but not by another. This chapter explores the evaluative nature of entrepreneurial constraints. Based on the cognitive appraisal framework (Lazarus & Folkman, 1984) – which argues that constraints are not the direct precipitating cause of a behavior, but rather the person’s appraisal of challenge and threat that determines the response – this chapter argues that distinct appraisals (i.e., challenge vs threat) of a same entrepreneurial constraint will be associated with distinct degrees of effort from entrepreneurs (i.e., enhanced vs reduced, respectively). This chapter provides a useful framework for entrepreneurship scholars to study the nuanced effect of entrepreneurial constraints on entrepreneurs’ behavior.