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Computer vision (CV) offers a promising approach to transforming the conventional in-person inspection practices prevalent within the construction industry. However, the reliance on centralized systems in current CV-based inspections introduces a vulnerability to potential data manipulation. Unreliable inspection records make it challenging for safety managers to make timely decisions to ensure safety compliance. To address this issue, this paper proposes a blockchain (BC) and CV-based framework to enhance safety inspections at construction sites.

This study adopted a BC-enhanced CV approach. By leveraging CV and BC, safety conditions are automatically identified from site images and can be reliably recorded as safety inspection data through the BC network. Additionally, by using this data, smart contracts coordinate inspection tasks, assign responsibilities and verify safety performance, managing the entire safety inspection process remotely.

A case study confirms the framework’s applicability and efficacy in facilitating remote and reliable safety inspections. The proposed framework is envisaged to greatly improve current safety inspection practices and, in doing so, contribute to reduced accidents and injuries in the construction industry.

This study provides novel and practical guidance for integrating CV and BC in construction safety inspection. It fulfills an identified need to study how to leverage CV-based inspection results for remotely managing the safety inspection process using BC. This work not only takes a significant step towards data-driven decision-making in the safety inspection process, but also paves the way for future studies aiming to develop tamper-proof data management systems for industrial inspections and audits.

Recently, the role of consumers in firms' innovation processes has increased. Prior literature asserts that qualitative aspects of consumers serve as crucial factors shaping the even competitiveness of a specific industry. This study focuses on measuring home demand conditions that enhance local firms' innovation.

The present study describes the development of a 12-item measure to assess consumer sophistication in the food industry. The items assess the general knowledge, experience, skills and abilities needed to purchase a specific food category. A second-order construct with three distinct first-order constructs emerged, which were termed opinion formulation, sensitivity and exposure with variety. The reliability and validity of the scale were assessed with pilot survey data using exploratory and confirmatory factor analyses. The developed measure was tested to investigate its effect on individuals' grocery buying behaviors using grocery receipt panel data from 723 consumers.

The results indicate that consumer sophistication has a positive effect on new and the variety of grocery purchases. The more sophisticated a consumer is, the more they buy new and a variety of products. The newly developed consumer sophistication measure has a variety of potential applications to predict consumers' variety-seeking and new product purchase behavior.

This study is the first to develop a measure for assessing demand quality, namely, consumer sophistication of a specific food product. This approach may offer insights to practitioners regarding the relevant consumer sophistication levels to target when launching a new product or service in the food industry.

The purpose of this paper is to investigate the effect of formulation categories (parent brand and extension product) and research and development (R&D) cooperation types on electronic word-of-mouth (eWOM) volume for extension products.

This study uses data from 109 extension products in the Korean dessert market whose formulations were changed between 1 February 2014 and 19 February 2019. The formulation categories and R&D cooperation types are transformed into dummy variables to conduct a linear regression.

The formulation categories and R&D cooperation types play key roles in proliferating eWOM for formulation change products. The most effective way to proliferate eWOM is through product extension by changing the formulation of ice cream, beverage and snack category products. Furthermore, vertical R&D cooperation positively affects the proliferation of products' eWOM.

These findings contribute to increasing the chance of successful food product development by providing information on the formulation changes that are effective at inducing consumers' interest.

This study aims to address how the social structure of the hospitality management field has evolved from 1960 to 2016.

The informal social structure of the hospitality management literature was analyzed by collecting authorship data from seven hospitality management journals. Co-authorship analyses via network analysis were conducted.

According to the findings, throughout the history of hospitality management, international collaboration levels are relatively low. Based on social network analysis, the research community is only loosely connected, and the network of the community does not fit with the small-world network theory. Additional findings indicate that researchers in the hospitality management literature are ranked via degree centrality, closeness centrality and betweenness centrality. Cliques, which contain at least five researchers, and core researchers are identified.

This study helps both scholars and practitioners improve the informal structure of the field. Scholars must generate strong ties to strengthen cross-fertilization in the field; hence, they collaborate with authors who have strong positions in the field. Specifically, this provides a useful performance analysis. To the extent that institutions and individuals are rewarded for publications, this study demonstrates the performance and connectivity of several key researchers in the field. This finding could be interesting to (post)graduate students. Hospitality managers looking for advisors and consultants could benefit from the findings. Additionally, these are beneficial for journal editors, junior researchers and agencies/institutions.

As one of the first study in the field, this research examines the informal social structure of hospitality management literature in seven journals.

This paper aims to explore the perceived impact of packaging logistics on the efficiency of freight transportation (EOT), and examine the interaction and relationship between packaging logistics and EOT.

The paper set up the conceptual model with seven hypotheses from the findings of previous literatures, and this model was tested with data and SEM.

The paper provided empirical insights about the perceived impact of packaging logistics on EOT and clarified the relative impact levels in the relationship between packaging logistics and EOT.

In spite of the chosen research approach, the perceived impact of information system on EOT may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions in further studies.

Findings of this study can be used by practioners to improve EOT and by researchers to investigate further studies.

The paper fulfilled a need from previous literatures to clarify the interaction and relationship between packaging logistics and EOT.

This study focuses on perceived overload from environmental stimuli and individual psychology and behavioral interactions. It constructs a theoretical model with overload as the key stressor based on the stressor-strain-outcome (SSO) model. The authors argue that system feature overload (SFO), information overload, and social overload lead to two psychological strains: fear of missing out (FoMO) and fatigue among users of short video platforms, affecting their discontinuous usage intentions.

To test the hypotheses, the authors conducted a questionnaire survey on 412 users' short video platform usage and empirically tested the constructed model using the research tool SmartPLS 3.3.2.

The results of data analysis showed that most of the hypotheses were supported. Specifically, system feature overload, information overload and social overload all positively affected FoMO. However, SFO and information overload significantly affected fatigue. There was no significant relationship between social overload and fatigue. In addition, both FoMO and fatigue negatively influenced users' discontinuous usage intentions.

The current research on user behavior in information systems tends to focus on the influence in the positive direction and less on the negative direction. The research on discontinuous usage intention (DUI) is a very new research topic. This research studies the influencing factors of users' discontinuous behavior from the perspective of perceptual overload. It provides a unique view for future short video platform user behavior research, with significant theoretical contributions and essential practice for short video platform operators to improve services.

It is essential to level the drilling platform across which a drilling robot travels in a slant underground coal mine tunnel to ensure smooth operation of the drill rod. However, existing leveling methods do not provide dynamic performance under the drilling conditions of the underground coal mine. A four-point dynamic leveling algorithm is presented in this paper based on the platform attitude and support rod displacement (DLAAD). An experimental drilling robot demonstrates its dynamic leveling capability and ability to ensure smooth drill rod operations.

The attitude coordinate of the drilling robot is established according to its structure. A six-axis combined sensor is adopted to detect the platform attitude, thus revealing the three-axis Euler angles. The support rod displacement values are continuously detected by laser displacement sensors to obtain the displacement increment of each support rod as needed. The drilling robot is leveled according to the current support rod displacement and three-dimensional (3 D) attitude detected by the six-axis combined sensor dynamically.

Experimental results indicate that the DLAAD algorithm is correct and effectively levels the drilling platform dynamically. It can thus provide essential support in resolving drill rod sticking problems during actual underground coal mine drilling operations.

The DLAAD algorithm supports smooth drill rod operations in underground coal mines, which greatly enhances safety, reduces power consumption, and minimizes cost. The approach proposed here thus represents considerable benefits in terms of coal mine production and shows notable potential for application in similar fields.

The novel DLAAD algorithm and leveling control method are the key contributions of this work, they provide dynamical 3 D leveling and help to resolve drill rod sticking problems.

This paper aims to propose a conceptual scale model of mobile drilling robot according to the actual drilling rig and working conditions to improve the safety and automation of drilling in tunnel construction and coal mining applications.

A couple of pinion and rack serves as the support mechanism driven by a motor with low rotation speed at high power, and these components are assembled in the center of the robot to tightly fasten the whole body together. The drilling rod and the sleeve are connected through a hole with screw thread so that the rod feeds and rotates simultaneously along with the sleeve. The robot model is automatically controlled by a single-chip microcomputer, and the anti-disturbance circuit is designed as well. A five-step rule obstacle avoidance method is proposed to ensure safe and reliable movement.

The results of simulation experiments on drilling operation do indicate that the mechanism and control method are feasible and effective.

The robot is nearly complete but indeed remains only an experimental machine.

The design of the mechanism structure for the conceptual robot is novelty. The method of five-step rule obstacle avoidance can improve reliability of obstacle avoidance according to the experimental results, which can meet the requirements of complex working conditions underground coal mine.

During drilling in coal mines, sticking of drill rod (referred to as SDR in this work) is a potential threat to underground safety. However, no practical measures to deter SDR have been developed yet. The purpose of this study is to develop an anti-SDR strategy using proportional-integral-derivative (PID) and compliance control (PIDC). The proposed strategy is compatible with the drilling process currently used in underground coal mines using drill rigs. Therefore, this study aims to contribute to the PIDC strategy for solving SDR.

A hydraulic circuit to reduce SDR was built based on a load-independent flow distribution system, a PID controller was designed to control the inlet hydraulic pressure of the rotation motor and a typical compliance control approach was adopted to control the feed force and displacement. Moreover, the weight and optimal combination of the alternative admittance control parameters for the feed cylinder were obtained by adopting the orthogonal experiment approach. Furthermore, a fuzzy admittance control approach was proposed to control the feed displacement. Experiments were conducted to test the effectiveness of the proposed method.

The experimental results indicated that the PIDC strategy was appropriate and effective for controlling the rotation motor and feed cylinder; thus, the proposed method significantly reduces the SDR during drilling operations in underground coal mines.

As the PIDC strategy solves the SDR problem in underground coal mines, it greatly improves the safety of coal mine operation and decreases the power cost. Consequently, it brings the considerable benefits of coal mine production and vast application prospects in other corresponding fields. Actual drilling conditions are difficult to accurately simulate in a laboratory; thus, for future work, drilling experiments can be conducted in actual underground coal mines.

The PIDC-based anti-SDR strategy proposed in this study satisfactorily controls the rotation motor and feed cylinder and facilitates the feed and rotation movements. Furthermore, the tangible novelty of this study results is that it improves the frequency response of the entire drilling system. The drilling process with PIDC decreased the occurrence of SDR by 50%; therefore, the anti-SDR strategy can significantly improve the safety and efficiency of underground coal mining.

Does the history of the bureaucratic system, along with the establishment of the Great Wall during the Ming and Qing dynasties (1368–1911), affect firm behavior across the borderlands of the Great Wall?

The Ming and Qing dynasties built a centralized administrative system in the borderlands on the south side of the Great Wall, in contrast to the “feudal lordship” system on the north side. Employing a regression discontinuity analysis framework with the Great Wall as a geographical discontinuity, we examine the long-run effects of the Great Wall on firms’ earnings management.

Using a large sample of nonlisted firms in the central core frontier region, we show that the earnings management of firms in the region south of the Great Wall is significantly curtailed compared with firms in the north of it, and this effect is more pronounced for non-SOEs. Our findings are robust to a battery of tests to account for alternative explanations.

Overall, by emphasizing the role of institutions, like legal system, shaped in history on firms’ earnings management, this study sheds new light on institutional determinants of firms’ behaviors in earnings information disclosure.

First, we enrich our understanding of the institutional determinants of firms’ financial reporting outcomes. Second, our findings shed new light on the long-term effects of historical ruling styles on modern corporate behavior.