Search results

As organizations globalize, they are facing twin challenges of (1) how to develop actionable intelligence from the vast amount of data flowing into their organization and (2) how to effectively manage the increasing risks to their supply chain. Therefore, the purpose of this paper is to bring these two issues on a single platform to understand how firms can effectively predict supply chain risk by developing and using BDA capabilities, through an automated risk alert tool.

The authors used a questionnaire-based survey methodology supported by secondary data to collect information related to managerial perceptions on how firms can develop a risk alert tool by improving BDA capabilities. A database of 213 senior and middle-level managers was developed and used to test the proposed hypothesis. Using econometric techniques, the authors identify the conditions necessary for such an automated risk management tool to be effective.

The results suggest that if organizations focus on developing an effective IT infrastructure supported by a strong BDA capability, they will be able to leverage these capabilities to develop an effective risk management tool. Moderating influences of Upstream and Downstream Supply Chain IT Infrastructure capabilities were also observed on different types of BDA capabilities within a firm. In conclusion, it was argued that the effectiveness of a risk alert tool is dependent on how well firms harness big data analytics capability.

The value of the research stems from the fact that it uses managerial surveys to identify specific BDA capabilities that can enable firms to develop risk resilience capabilities. In addition, the article is one of the few empirical studies that aims to identify how firms can use BDA capabilities within a supply chain context to develop an automated risk alert tool. The article, therefore, contributes to the literature that identifies the value of BDA capabilities within the context of supply chain risk management.

This study mainly aims to explore the causal nexus between big data-driven organizational capabilities (BDDOC) and supply chain innovation capabilities (SCIC) and innovation performance (IP), then explore the indirect effect of SCIC and also test the moderating effects for both internal supply chain integration (ISCI) and external supply chain integration (ESCI) into the relationship between BDDOC and SCIC.

In order to test the conceptual model and the hypothesized relationships between all the constructs, the data were collected using a self-reported questionnaire by workers in Jordanian small and medium manufacturing enterprises. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the model.

The paper reached a set of interesting results where it was confirmed that there is a positive and statistically significant relationship between BDDOC, SCIC and IP in addition to confirming the indirect effect of SCIC between BDDOC and IP. The results also showed that there is a moderating role for both ESCI and ISCI.

This study can be considered the first study in the current literature that investigates these constructs as shown in the research model. Therefore, the paper presents an interesting set of theoretical and managerial contributions that may contribute to covering part of the research gap in the literature.

Educational policies, integrated practices, obliged strategies and notable benchmarks are always required by the higher educational institutions (HEIs) for operating business ventures into competent boundaries and to preside toward the overall new business density. The same are needed to be evaluated based on student's concerns for road-mapping sustainability. Accordingly, authors conducted present study to identify crucial quality characteristics (measures) under the origins of HEIs based on student's concerns using qualitative medium under Indian economy. The study is presenting critical dimensions and quality characteristics, which are seeking by the students for selecting HEIs for their studies.

Kano integrated-Grey-VIKOR approach is utilized in present study for road-mapping sustainability based on the determination of priority index and ranking. The study utilized three segments of methodology, where in the first segment, Kano technique is implicated to define priority index of quality characteristics. In the second segment, grey sets theory is implicated to capture the perceptions of the respondents. In the third segment, VIKOR technique is implicate to rank the HEIs.

The findings of the study will assist administrators in planning the prominent strategies that can embrace performance traits under HEI, which in turn will participate in growth and development of an economy. The findings have revealed “PPCS, ICMC, TSTR, PICM, AFEP, IMIS as Attractive performance characteristics,” “IEAF, OIAR, INET as One dimensional performance characteristics,” “QTCS, PORE, SIRD as Must-be performance characteristics” and “PQPE, PCTM as Indifferent performance characteristics.” Additionally, “Professional and placement characteristics of institute” is found as the most significant measure inspiring students for admiring engineering institutes. It is found that “Observance of institutional affiliation and recognition” and “Infrastructure, classroom management and control methods” are found as the second significant measures. “Patterns of question papers and evaluation medium” and “Personal characteristics of teacher and management” are found as the least competent characteristics admiring stakeholders for selecting HEI.

The present study can assist administrators in drafting refined policies and strategies for practising quality outputs by HEI. The study suggested critical quality characteristics, which in respond will aid in attracting more number of students toward educational institutes. A study under Indian context is demonstrated for presenting critical facts and attaining higher student's enrolment rates.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

This study investigates the impact of big data analytics capabilities on export performance. Moreover, it assesses the mediating effect of the supply chain innovation and moderating effect of supply chain agility.

This study is based on primary data that were collected from the manufacturing sector operating in Jordan. A total of 327 responses were used for the final data analysis. Data analysis was performed via a partial least square structural equation modeling (PLS-SEM) approach.

The results of the data analysis supported a positive relationship between big data analytics capabilities and the export performance as well as a mediating effect of supply chain innovation. It was confirmed that supply chain agility moderated the relationship of supply chain innovation and export performance.

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, export performance, supply chain innovation and supply chain agility. This study offers new theoretical and managerial contributions that add value to the supply chain management literature by testing the moderated-mediated model of these constructs in the manufacturing sector in Jordan.

Online production and transmission of child abuse material (CAM) is a complex and growing global problem. The exponential increase in the volume of CyberTips of CAM offending is placing information processing and decision-making strains on law enforcement. This paper presents the outcomes of a project that reviewed an existing risk assessment tool and then developed a new tool for CAM triaging and investigative prioritisation.

Using a mixed method approach, the authors first explored the capacity of an existing risk assessment tool for predicting a police action. The authors then used these findings to design and implement a replacement CAM decision support tool. Using a random sample of CyberTip alert cases from 2018, the authors then tested the efficiency of the new tool.

The existing risk assessment tool was not fit for CAM triaging purposes. Just six questions from the old tool were found to be statistically and significantly associated with law enforcement agents achieving a police action. The authors found that an immediate threat of abuse/endangering a child, potential case solvability, CAM image assessment, chat assessment, criticality and some weighting for professional judgement were significant in being associated with a police action. The new decision support tool is more efficient to complete and achieved a 93.6% convergence of risk ratings with the old tool using 2018 case data.

This research is unique in its development of an evidence-based decision support tool that enhances the ability of law enforcement agents to objectively and efficiently triage and prioritise increasing numbers of CyberTip alerts.

Reports on the authors' experience with a patient safety quality improvement program, intended to reduce the incidence and severity of adverse outcomes for emergency department (ED) patients aged ≥75. The Identification of Seniors at Risk scale was used for screening, and those at high risk were referred for appropriate intervention. The plan‐do‐study‐act improvement cycle was followed, conducting process evaluation to diagnose and correct implementation difficulties. Reports that: implementing an ED screening and referral program is deceptively difficult; process evaluation multidisciplinary working group meetings are an essential improvement tool; screening inclusion criteria had to be adapted to the subject population in order to make efficient use of staff time; the screening questions and process required ongoing assessment, revision, and local adaptation in order to be useful; and high‐risk screening in the ED is critical to a hospital system's ability to anticipate clinical problems; the plan‐do‐study‐act improvement cycle is a practical and useful tool for improving quality and systems in a real care setting.

The purpose of this paper is to explore two distinct yet complimentary “structured professional judgement (SPJ)” approaches to terrorist/extremist risk assessment on the vexing issue of how best to deal with the subjectivity inherently involved in professional judgement.

An SPJ methodology is considered the best practice approach for assessing terrorism risk. Currently there are four specific terrorism risk instruments that have been published in the literature. Two of these SPJ tools are examined in detail, namely the Violent Extremist Risk Assessment tool (Pressman, 2009; Pressman et al., 2012) and the Structured Assessment of Violent Extremism (SAVE) tool (Dean, 2014). The paper critically unpacks the conceptual and methodological stumbling blocks of an SPJ methodology for controlling human subjectivity.

The paper presents the case for adopting a “controlling in” approach rather than a “controlling out” approach of an analyst’s subjective tacit (in-the-head) knowledge inherent in their professional judgement. To have a quantifiable SPJ tool that triangulates the multi-dimensionality of terrorism risk which can validate an analyst’s professional judgement is the next logical step in terrorist/extremist risk assessment work. The paper includes a case example of this “controlling in” approach and the validation methodology used by the SAVE software system.

The implications for practice range from incorporating the SAVE system in operational policing/national security work with its quantitative nature, triangulated risk scores, visualisation output of a prioritised case report with in-built alerts, to the required training for system calibration to enhance user proficiency.

This is a highly original and innovative paper as this type of quantified SPJ tool (SAVE) has up until now never been applied before in terrorist/extremist risk assessment work.

Security information management (SIM) has emerged recently as a strong need to ensure the ongoing security of information systems. However, deploying a SIM and the associated sensors is a challenge in any organization, as the complexity and cost of such a project are difficult to bear. This paper aims to present an architecture for outsourcing a SIM platform, and discuss the issues associated with the deployment of such an environment.

The paper is an overview of the typical SIM and a possible architecture for its outsourcing.

The paper explains that the day‐to‐day operation of a SIM is beyond the financial capabilities of all but the largest organizations, as the SIM must be monitored constantly to ensure timely reaction to alerts. Many managed security services providers (MSSP), therefore, propose outsourcing the alert management activities. Sensors are deployed within the customer's infrastructure, and the alerts are sent to the outsourced SIM along with additional log information.

The paper illustrates that intrusion detection and SIM as two important and active research domains for information systems security.

To explain how progressive companies are using a combination of knowledge and risk management (KRM) systems and techniques in order to help them to prevent, or respond most effectively to, ethical or reputation‐damaging incidents.

The paper explains KRM, develops a corporate integrity framework, and then explores how the KRM process component of the framework is related to the use of knowledge management (KM)‐related procedures, techniques, and tools in use in many corporations.

In many forward‐looking corporations KM procedures, techniques and tools are being used to perform risk management. KRM, the integration of knowledge and risk management, is alive and well and, given the global importance of risk management, may provide KM with a much‐needed and revitalizing boost.

The value of the KRM perspective is its development of a new and comprehensive application of KM to the vital global corporate need of risk management.