Search results

This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions.

The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective.

Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection.

This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.

The purpose of this paper is to provide an overview of the trends and challenges relating to research into the human aspects of ransomware.

A systematic mapping study was carried out to investigate the trends in studies into the human aspects of ransomware, identify challenges encountered by researchers and propose directions for future research. For each of the identified papers from this study, the authors mapped the year of publication, the type of paper, research strategy and data generation method, types of participants included, theories incorporated and lastly, the authors mapped the challenges encountered by the researchers.

Fifty-nine papers published between 2006 and 2022 are included in the study. The findings indicate that literature on the human aspects of ransomware was scarce prior to 2016. The most-used participant groups in this area are students and cybersecurity professionals, and most studies rely on a survey strategy using the questionnaire to collect data. In addition, many papers did not use theories for their research, but from those that did, game theory was used most often. Furthermore, the most reported challenge is that being hit with ransomware is a sensitive topic, which results in individuals and organisations being reluctant to share their experiences.

This mapping study reveals that the body of literature in the area of human aspects of ransomware has increased over the past couple of years. The findings highlight that being transparent about ransomware attacks, when possible, can help others. Moreover, senior management plays an important role in shaping the information security culture of an organisation, whether to have a culture of transparency or of secrecy.

This study is the first of its kind of systematic mapping studies contributing to the body of knowledge on the human aspects of ransomware.

The aim of this study is to analyze the differences between non-standard forms of employment (FoE) (i.e. dependent self-employment/business-to-business/B2B contract and contract of mandate) in terms of investing in the development of future competencies by employees and employers. This study also examined additional factors which influence these investments.

To collect data, the computer-assisted telephone interview technique was used. 200 employees from different companies located in Poland participated in this study, wherein each of the above-mentioned FoEs (i.e. dependent self-employment and contract of mandate) was represented by 100 people. The Chi-Square test and multivariate logistic regression analysis were used in the statistical analyses.

In the case of only 2 out of 14 competencies, there were statistically significant differences between the two groups of respondents: the employers financed training courses for B2B employees more frequently than for mandate contract workers. Moreover, in only one case there was a statistically significant difference: the self-employed financed training courses themselves more often than mandate contract workers. This study revealed an important impact of other variables such as respondents’ age, education level, parental status and industry on the training activities undertaken by employers and employees.

Although the issue of developing future competencies is important, there is little research examining this problem in the context of people who work in non-standard FoE. Moreover, previous research primarily focused on identifying differences between people working under employment contracts and the self-employed. This article fills these research gaps as well as shows that more factors should be considered in the research models to get a deeper insight into the problem of non-standard FoEs.

This study investigates the barriers to adopting green human resource management (GHRM) under uncertain conditions by integrating the resource-based view (RBV) and stakeholder theory.

A board of experts, which consisted of 28 practitioners and two academics, was invited to participate in the research. The fuzzy Delphi and fuzzy decision-making trials and evaluation laboratory were utilized to achieve the study's objectives.

The findings indicate that barriers encompass 14 criteria and five attributes. Among the 14 criteria, the banking industry's lack of green culture, lack of trust in green benefits, employee's capacity to change, lack of support from top management and absence of a comprehensive plan to implement GHRM are significant barriers. The attributes are management, human resources, organizational, regulatory and customer barriers.

Implementing GHRM in Indonesian banking necessitates practical policies and gradual adaptation strategies. Companies should establish standard operating procedures, reward systems and periodic habit changes to embed green practices effectively.

This study is among the first to employ stakeholder theory and the RBV in examining the barriers to green human resources adoption in the banking industry.

During a fall, a significant part of the major forces is absorbed by the dorsolumbar column area. When the applied stresses exceed the yield strength of the bone tissue, fractures can occur in the vertebrae. Vertebral fractures constitute one of the leading causes of trauma-related hospitalizations, accounting for 15% of all admissions. Posterior pedicle screw fixation has become a common method for treating burst fractures. However, physicians remain divided on the number of fixed segments that are needed to improve clinical outcomes. The present work aims to understand the biomechanical impact of different fixation methods, improving surgical treatments.

A finite element model of the dorsolumbar spine (T11–L3) section, including cartilages, discs and ligaments, was created. The dorsolumbar stability was tested by comparing two different surgical orthopedic treatments for a fractured first lumbar vertebra on the L1 vertebra: the posterior short segment fixation with intermediate screws (PSS) and the posterior long segment fixation (PL). Distinct loads were applied to represent daily activities.

Results show that both procedures provide acceptable segment fixation, with the PL offering less freedom of movement, making it more stable than the PSS. The PL approach can be the best choice for an unstable fracture as it leads to a stiffer spine segment.

This study introduces a novel computational model designed for the biomechanical analysis of dorsolumbar injuries, aiming to identify the optimal treatment approaches within both clinical and surgical contexts.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

Today, companies are struggling to develop their human resources analytics (HRA) capability, although interest in the subject is rapidly increasing. Furthermore, the academic literature on the subject is immature with limited practical guidance or comprehensive models that could support organisations in the development of their HRA capability. To address this issue, the aim of this paper is to provide a maturity model – i.e. HRAMM – and an interdependency matrix through which an organisation can (1) operationalise its HRA capability and assess its organisational maturity; (2) generate harmonious development roadmaps to improve its HRA capability; and (3) enable benchmarking and continuous improvement.

The research described in this paper is based on the popular methodology proposed by Becker et al. (2009) and the procedure for maturity evaluation developed by Gastaldi et al. (2018). This method combines academic rigour and field experience in analytics, in a process spanning eight main phases that involves literature reviews and knowledge creation techniques.

We define HRA maturity through four areas and 14 dimensions, providing a comprehensive model to operationalise HRA capability. Additionally, we argue that HRA maturity develops through an evolutionary path described in four discrete stages of maturity that go beyond traditional analytics sophistication. Lastly, the interdependency matrix reveals specific enablers for the development of HRA.

This paper provides practitioners with useful tools to monitor, evaluate and plan their HRA development path. Additionally, our research helps practitioners to prioritise their work and investment, generating an effective roadmap for developing and improving their HRA capability.

To the best of the authors’ knowledge, this study is the first to provide a model for evaluating the maturity of HRA capability plus an interdependency matrix to evaluate systematically the prerequisites and synergies among its constituting dimensions.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

The paper has a twofold purpose: (1) to test the application of means-end theory to providers of hospitality goods and services, and (2) to explore this question in the context of winery tasting rooms when they had a unique opportunity to restructure their hospitality experience due to government restrictions in response to COVID.

A qualitative approach was adopted, and a convenience sample was used to conduct semi-structured laddering interviews. Forty interview transcripts were coded as means-end ladders, which were analyzed using a custom computer program to develop the implication matrix and the hierarchical value map.

This paper demonstrates that means-end is a useful approach to investigate the values and behaviors of the producer, specifically hospitality hosts. It finds that the principal goal of tasting rooms is to generate sales, and offering a compelling guest experience is the characteristic that contributes the most to achieving that goal. The staff and the atmosphere created for the guests are the two factors with the greatest influence on the guest experience.

This is the first paper to use means-end theory to study the hospitality host, or the producer of goods and services in general, and the first to study winery hospitality primarily through the lens of means-end theory. The study also helps fill a gap in research on tasting room sales focused on the winery’s goals.