Search results

This study aims to address the current gap in knowledge of indirect procurement performance management. It attempts to argue the need for a specific and tailored performance management approach for the indirect procurement function that incorporates a balanced approach, beyond financial measures.

The case study approach evaluated key performance indicators from a balanced scorecard (BSC) perspective in the development of a performance measurement system (PMS) for a Middle Eastern university’s indirect procurement division. It initially reviewed the literature to assess potential indicators for this context. It used vision and mission statement analysis alongside expert interviews to augment the literature. The candidate indicators were then evaluated and ranked by an expert panel through applying a four-round Delphi technique.

Twenty-nine procurement-specific indicators are suggested in a BSC framework. The five highest-ranked indicators were not in the financial perspective unlike other BSC studies in the broader field of supply chain management (SCM).

The study suggests a framework and indicators for a procurement PMS for practitioners to consider. It also highlights there is no one-size-fits-all and that organisations need to tailor PM to the organisation and divisional strategy and operational needs. This study aids the development of guidelines for executives and procurement management that wish to develop indicators and a PMS.

This study contributes to knowledge by partly addressing the under-researched field of indirect procurement PM. The literature suggested that various roles in SCM require specific PM indicators. This study puts forward a BSC framework with 29 indicators specifically for indirect procurement. Fourteen of these indicators were derived from non-literature sources. This study enhances knowledge and contributes to the limited debate and evidence on indirect procurement PM and the broader PM literature.

Despite its significance, research on how attribute framing affects ordering decisions in dual sourcing remains insufficient. Hence, this study investigated the effects of attribute framing in a sourcing task involving certain and uncertain qualities of two suppliers and analysed the role of attention with respect to suppliers' information in framing effects.

The impacts of attribute framing on sourcing decisions were demonstrated in two online between-subject (2 × 2 factorial) experimental studies involving professional samples. Study 2 was an eye-tracking experiment.

In Study 1 (N = 251), participants presented with a “high-quality” rather than a “low-quality” frame made different sourcing decisions, opting for larger percentage of order(s) from a supplier under the “high-quality” frame. This pattern holds true for suppliers who differ in risk. This finding was replicated in Study 2 (N = 129). Attention asymmetry related to the information on supplier quality contributes to this effect. Attention directed towards information regarding the supplier's quality under a positive frame mediated the relationship between attribute framing and sourcing decisions.

Highlighting the positive attributes of a risky supplier is essential when ordering from the risky supplier is an optimal decision. It is advantageous for suppliers to highlight positive rather than negative attributes when describing the quality of their components against others.

This is the first study to examine the effect of attention on the relationship between attribute framing and dual sourcing. This presents a new behavioural perspective wherein managers' attention to information plays a vital role.

The purpose of this study is to investigate the pivotal role of environmental innovations in driving sustainability practices within medium and large manufacturing firms operating in Uganda.

Using a cross-sectional and quantitative methodology, data were collected through a questionnaire survey involving 208 manufacturing companies. The smart partial least squares path modelling technique was used for the analysis.

The analysis unveils significant and positive associations. Specifically, product innovation exhibits a robust and affirmative relationship with sustainability practices. Similarly, the correlation between process innovation and sustainability practices emerges as statistically significant. Moreover, the findings underscore the noteworthy and constructive predictive influence of environmental innovation on sustainability practices.

These empirical results present substantial implications for theoretical frameworks and practical applications. From a policy perspective, the findings emphasise the importance of incentivising eco product and eco process innovations as potential drivers of eco-friendly practices. On the managerial front, strategic resource allocation and the adoption of integrated environmental innovation strategies are advocated, with the ultimate goal of enhancing sustainable business approaches within Uganda’s manufacturing subsector.

To the best of the authors' knowledge, this study represents the inaugural attempt to investigate the role of environmental innovations in elucidating sustainability practices within a least developed country. Notably, while all dimensions demonstrate significance, it is noteworthy that product innovation emerges as the more substantial contributor to the promotion of sustainability practices.

Cloud computing (CC) refers to the usage of virtualization technology to share computing resources through the internet. Task scheduling (TS) is used to assign computational resources to requests that have a high volume of pending processing. CC relies on load balancing to ensure that resources like servers and virtual machines (VMs) running on real servers share the same amount of load. VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data.

VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data. With a large number of VM or jobs, this method has a long makespan and is very difficult. A new idea to cloud loads without decreasing implementation time or resource consumption is therefore encouraged. Equilibrium optimization is used to cluster the VM into underloaded and overloaded VMs initially in this research. Underloading VMs is used to improve load balance and resource utilization in the second stage. The hybrid algorithm of BAT and the artificial bee colony (ABC) helps with TS using a multi-objective-based system. The VM manager performs VM migration decisions to provide load balance among physical machines (PMs). When a PM is overburdened and another PM is underburdened, the decision to migrate VMs is made based on the appropriate conditions. Balanced load and reduced energy usage in PMs are achieved in the former case. Manta ray foraging (MRF) is used to migrate VMs, and its decisions are based on a variety of factors.

The proposed approach provides the best possible scheduling for both VMs and PMs. To complete the task, improved whale optimization algorithm for Cloud TS has 42 s of completion time, enhanced multi-verse optimizer has 48 s, hybrid electro search with a genetic algorithm has 50 s, adaptive benefit factor-based symbiotic organisms search has 38 s and, finally, the proposed model has 30 s, which shows better performance of the proposed model.

User’s request or data transmission in a cloud data centre may cause the VMs to be under or overloaded with data. To identify the load on VM, initially EQ algorithm is used for clustering process. To figure out how well the proposed method works when the system is very busy by implementing hybrid algorithm called BAT–ABC. After the TS process, VM migration is occurred at the final stage, where optimal VM is identified by using MRF algorithm. The experimental analysis is carried out by using various metrics such as execution time, transmission time, makespan for various iterations, resource utilization and load fairness. With its system load, the metric gives load fairness. How load fairness is worked out depends on how long each task takes to do. It has been added that a cloud system may be able to achieve more load fairness if tasks take less time to finish.

This study examines how carbon tools, including carbon accounting and management tools, can be created, used, modified and linked with other traditional management controls to materialise and effectuate organisations’ response strategies to multiple interacting logics in carbon management and the role of sustainability managers in these processes.

This study utilises the construct of accounting toolmaking, which refers to practices of adopting, adjusting and reconfiguring accounting tools to unfold how carbon tools are used as means to materialise responses to multiple interacting carbon management logics. It embraces a field study approach, whereby 38 sustainability managers and staff from 30 organisations in New Zealand were interviewed.

This study finds that carbon toolmaking is an important means to materialise and effectuate organisations’ response strategies to multiple interacting carbon management logics. Four response strategies are identified: separation, selective coupling, combination and hybridisation. Adopting activity involves considering the additionality, detailing, localising and cascading of carbon measures and targets and their linkage to the broader carbon management programme. In adjusting carbon tools, organisations adapt the frequency and orientation of carbon reporting, intensity of carbon monitoring and breadth of carbon information sharing. Through focusing on either procedural sequencing, assimilating, equating or integrating, toolmaking reconfigures the relationship between carbon tools and traditional management control systems. Together, these three toolmaking activities can be configured differently to construct carbon tools that are fit for purpose for each response strategy. These activities also enact certain roles on sustainability managers in the process of representing, communicating and/or transferring carbon information knowledge, which also facilitate different response strategies.

The study demonstrates the various carbon toolmaking practices that allow organisations to handle the multiple interacting logics in carbon management. The findings provide suggestions for organisations on how to adopt, adjust and reconfigure carbon tools to better embed the ecological logic in organisations’ strategies and operations.

The authors identify how carbon toolmaking materialises and effectuates organisations’ responses to multiple interacting logics in carbon management.

The purpose of this study is to identify the possible efficiency gains in using tokenization for the execution of public expenditure on governmental investments.

Through design science research methodology, the exploratory research produced a tokenized prototype in the blockchain, through the Ernst and Young OpsChain traceability solution, allowing automated processes in the stages of public expense. A focus group composed of auditors from the public sector evaluated the possibility of improving the quality of information available in the audited entities, where the tokens created represent and register the actions of public agents in the blockchain Polygon.

The consensus of the experts in the focus group indicated that the use of tokenization could improve the quality of the information, since the possibility of recording the activities of public agents in the metadata of the tokens at each stage of the execution of the expenditure allows the audited entities the advantages of the information recorded on the blockchain, according to the following ranking: first the immutability of audited data, followed by reliability, transparency, accessibility and efficiency of data structures.

This research makes an empirical contribution to the real use of tokenization in blockchain technology to the public sector through a value chain in which tokens were created and moved between the wallets of public agents to represent, register and track the operations regarding public expense execution.

The purpose of this study is to explore the potential for technical accounting resources to help professional accountants exercise their performative agency.

The authors combine the integrative learning theory of truth and the concept of performativity, including two approaches to sustainability education and interventions, to construct a grid for coding the technical resources provided by the UK's Institute of Chartered Accountants in England and Wales, a pioneer in sustainability advocacy.

The findings suggest the dominance of the “predetermined and expert-determined” approach. They also reveal the emergence of three levels of performative topoi based on the relative presence of the “predetermined and expert-determined” and “process-of-seeking” approaches to professional interventions toward sustainability. The results show the profession's evolving contribution to the construction of actionable knowledge.

The main limitation of this research is that it draws on a limited corpus. In addition, the use of a binary code to represent the presence/absence of a code does not convey the code's quantitative importance.

The results are useful for those wanting to produce technical accounting resources that are more likely to help professionals build actionable knowledge and contribute to accountants' interventions toward sustainability.

Findings suggest the need for reflection on how the accounting profession can best contribute to implementing sustainability in organizations.

Few studies deconstruct professional technical resources to see how a profession can contribute to a process of societal change.

This study aims to reveal the contribution mechanism of various types of intrafirm networks formed among inventors to firms’ searching for new knowledge. This study also intends to show how this mechanism is influenced by the geographic dispersion of inventors and the external alliance of firms.

This study develops an analytical framework building on social network theory to explain the collective search among inventors within the firm. The authors validate the hypotheses using the data from 316 publicly traded biotechnology firms in the USA.

As demonstrated by the findings, intrafirm network clustering facilitates the search for new knowledge. The geographic dispersion of inventors’ location has a negative moderating effect on this relation, whereas the number of alliance partners has a positive moderating effect on this relation. By contrast, the search for new knowledge is hampered by the intrafirm network average path length. The geographic dispersion of inventors positively moderates this relation, whereas a firm’s alliance partner number negatively moderates this relation.

To the best of the authors’ knowledge, this study is the first to examine the joint effect of intrafirm networks, inventors’ geographic locations and external alliances on the new knowledge-searching process. This study points out that new knowledge acquired through inventors’ geographic locations and alliance partners is internalized efficiently according to different types of internal networks.

This paper aims to use artificial neural network (ANN) methods to predict stock price crashes in the Chinese equity market.

Three ANN models are developed and compared with the logistic regression model.

Results from this study conclude that the ANN approaches outperform the traditional logistic regression model, with fewer hidden layers in the ANN model having superior performance compared to the ANNs with multiple hidden layers. Results from the ANN approach also reveal that foreign institutional ownership, financial leverage, weekly average return and market-to-book ratio are the important variables when predicting stock price crashes, consistent with results from the traditional logistic model.

First, the ANN framework has been used in this study to forecast the stock price crashes and compared to the traditional logistic model in the world’s largest emerging market China. Second, the receiver operating characteristics curves and the area under the ROC curve have been used to evaluate the forecasting performance between the ANNs and the traditional approaches, in addition to some traditional performance evaluation methods.

This paper aims to examine the effect of the auditors’ burnout determinates on audit quality and performance. It also analyses whether the demographic characteristics of gender, age group, education and job positions affect auditors’ decisions for burnout, audit quality and performance.

A questionnaire was distributed on a sample of auditors in the top ten auditing firms in an emerging market including the Big 4. Factor analysis, correlation matrix and structural equation modeling were used for the analysis of the collected data and testing the developed hypotheses.

The results show that burnout has negative consequences for both the auditor and the auditing firm. While good organizational climate has a negative significant association with audit quality, nonethical decisions and audit performance, role clarity has positive significant association with the audit quality and performance and has an insignificant association with nonethical decisions. Also, turnover intention has significant positive association with nonethical decision, audit quality and performance.

This research is among the first to focus on auditor’s burnout determinates on audit quality and performance in an emerging market characterized by different socioeconomic, political and cultural factors compared with those of developed markets. Auditors, regulators and professional policymakers can benefit from the results of this research.