Search results

Several conceptual works suggest that more digitalized information systems in management accounting have the potential to make this corporate function more effective. Against this backdrop, this study aims to investigate the impact of information systems quality in management accounting on the effectiveness of management control systems. Additionally, this study examines the moderating effect of process automation.

A cross-sectional survey of 125 German Mittelstand firms and hierarchical regression analyses were used for data collection and analysis.

The findings confirm the assumed positive effect of information systems quality in management accounting on management control effectiveness. They also confirm the assumed moderating effect of process automation. The authors find that the relationship between information systems quality in management accounting and management control effectiveness is more pronounced if the firm features a higher degree of process automation.

Several earlier case studies and a few quantitative studies indicated the potentially positive effect of high-quality information systems in management accounting on management control effectiveness. To the best of the authors‘ knowledge, this study is among the first to deliver quantitative proof of this relationship in the context of German Mittelstand firms. Moreover, the authors add to this literature the moderating effect of process automation in the relationship between information systems quality in management accounting and management control effectiveness.

The information systems (IS) literature has indicated the importance of data analytics capabilities (DAC) in improving business performance in organizations. The literature has also highlighted the roles of organizations’ data-related resources in developing their DAC and enhancing their business performance. However, little research has taken resource quality into account when studying DAC for business performance enhancement. Therefore, the purpose of this paper is to understand the impact of resource quality on DAC development for business performance enhancement.

We studied DAC development using the resource-based view and the IS success model based on empirical data collected via 19 semi-structured interviews.

Our findings show that data-related resource (including data, data systems, and data services) quality is vital to the development of DAC and the enhancement of organizations’ business performance. The study uncovers the factors that make up each quality dimension, which is required for developing DAC for business performance enhancement.

Using the resource quality view, this study contributes to the literature by exploring the role of data-related resource quality in DAC development and business performance enhancement.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

This paper aims to analyze the impact of the adoption of ISO 14001 and ISO 9001 on the performance of Portuguese companies. The sample includes the companies listed on Euronext Lisbon, with economic, financial and specific information – the specific being environmental information and quality information – for the period between 2015 and 2019, which corresponds to the post-Troika period when some economic growth started to be witnessed. The specific information of each area is translated into the environmental certification by the ISO 14001 standard, the quality certification by the ISO 9001 standard, and sustainability reports.

To achieve this aim, four variables were used as a measure of the companies' performance, Return on Assets (ROA), Return on Equity (ROE); Tobin's Q and EBITDA Margin. With this data, different panel models were tested to validate if ISO 9001 and ISO 14001 certifications impact Portuguese listed companies performance. Specifically, the authors have used the Generalized Method of Moments, GMM-System, an estimation method proposed by Arellano and Bover (1995) and Blundell and Bond (1998).

The results show that, in general, the environment and quality variables fail to explain the dependent variables, that is, ISO certifications do not provide positive or negative variations in the performance of companies, suggesting that they are not yet as much for civil society, as well as for current or potential shareholders. When used as an independent variable, certification according to the ISO 14001 or 9001 standards, negative and significant oscillations were verified in the dependent variable, MgEBITDA, suggesting that only for managers this variable is determinant, but with a negative impact, given the high costs, it entails without pressure from other stakeholders.

This study is the first to analyze the impact of the adoption of ISO 14001 and ISO 9001 on Portuguese companies' performance. This empirical study aims to show all investors, managers, regulators and civil society itself the long path that still needs to be taken toward sustainability.

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by incorporating Industry 4.0 technological innovations into existing quality management frameworks, signifying a significant evolution in quality control systems. Despite the evident advantages, the practical deployment in the Indian manufacturing sector encounters various obstacles. This research is dedicated to a thorough examination of these impediments. It is structured around a set of pivotal research questions: First, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Second, it aims to elucidate these barriers' interrelations and mutual dependencies. Thirdly, the research prioritizes these barriers in terms of their significance to the adoption process. Finally, it contemplates the ramifications of these priorities for the strategic advancement of manufacturing practices and the development of informed policies. By answering these questions, the research provides a detailed understanding of the challenges faced. It offers actionable insights for practitioners and policymakers implementing Quality 4.0 in the Indian manufacturing sector.

Employing Interpretive Structural Modelling and Matrix Impact of Cross Multiplication Applied to Classification, the authors probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorized according to their driving power and dependence, providing a richer understanding of the dynamic obstacles within the Technology–Organization–Environment (TOE) framework.

The study results highlight the lack of Quality 4.0 standards and Big Data Analytics (BDA) tools as fundamental obstacles to integrating Quality 4.0 within the Indian manufacturing sector. Additionally, the study results contravene dominant academic narratives, suggesting that the cumulative impact of organizational barriers is marginal, contrary to theoretical postulations emphasizing their central significance in Quality 4.0 assimilation.

This research provides concrete strategies, such as developing a collaborative platform for sharing best practices in Quality 4.0 standards, which fosters a synergistic relationship between organizations and policymakers, for instance, by creating a joint task force, comprised of industry leaders and regulatory bodies, dedicated to formulating and disseminating comprehensive guidelines for Quality 4.0 adoption. This initiative could lead to establishing industry-wide standards, benefiting from the pooled expertise of diverse stakeholders. Additionally, the study underscores the necessity for robust, standardized Big Data Analytics tools specifically designed to meet the Quality 4.0 criteria, which can be developed through public-private partnerships. These tools would facilitate the seamless integration of Quality 4.0 processes, demonstrating a direct route for overcoming the barriers of inadequate standards.

This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE framework, detailing how these barriers interact with and influence each other, particularly highlighting the previously overlooked environmental factors. The analysis reveals a critical interdependence between “lack of standards for Quality 4.0” and “lack of standardized BDA tools and solutions,” providing nuanced insights into their conjoined effect on stalling progress in this field. Moreover, the study contributes to the theoretical body of knowledge by mapping out these novel impediments, offering a more comprehensive understanding of the challenges faced in adopting Quality 4.0.

Continuous improvement in an integrated approach is a philosophy developed over decades based on a set of management practices. It comprises enhancement methodologies that escalate success as well as diminishes letdowns. The state-of-the-art literature finds a variety of practices for the execution of continuous improvement (CI) system. However, it is rare to find an empirical study with an inclusive system that considers various practices in one frame for improving competitiveness. With this outlook, therefore, this study aims originally to identify drivers, motivations and barriers for the application of integrated CI system, and then conduct an empirical investigation within the context of Ethiopian manufacturing industries.

Justification of the problem, extensive review of literature, identification of practices, developing research framework, investigational analysis of the empirical study using reliability and descriptive statistical analysis and identifying leading drivers (unique practices and common factors), motivations and barriers are the research approaches used in this study. Furthermore, the primary data were collected through a self-administered questionnaire and were analyzed using a statistical package for social science (SPSS) 23 and the findings were triangulated to relate to the existing state-of-the-art literature.

The findings indicate 17 common factors associated with human, strategic, operational, technology, structure, resource and information factors; 21 unique practices of just-in-time (JIT), lean-six sigma (LSS), supply chain management (SCM), total productive maintenance (TPM), and total quality management (TQM) methodologies; 20 barriers connected with internal and external issues and 17 motivations linked to operational, innovation and business results are identified. In general, the empirical analysis discovers the practices are noteworthy and commonly supported by a least of 52% of the respondents. As a result, the first five prominent common factors, barriers, unique practices and motivations are also supported by a minimum of 72%, 73.9%, 65.8% and 75% of the respondents, respectively.

Even though this is the first-ever study in the Ethiopian manufacturing sector with the focus on integrated CI practices of JIT, TQM, TPM, SCM and LSS initiatives, some limitations have existed and the major limitations of the study are, targeted merely small number manufacturing companies despite the fact that there are hundreds of companies implementing CI system in Ethiopia, and the data collected were only based on the perception of the respondents, and other information’s like annual reports was not employed to support the findings.

The findings of this study underlined that the implementation of drivers in relation to common factors and unique practices supported by exterminating barriers in manufacturing industries of Ethiopia enables to enhance competitiveness through attaining operational, innovation and business results though it requires a practical case application to prove this perception-based analysis.

Though there are a number of studies published on integrated continuous improvement, currently it is found that there is no literature focused on the identification and empirical investigation of drivers (common factors and unique practices), motivations and barriers for application of integrated CI system with the focus of JIT, TQM, TPM, SCM and LSS initiatives. Therefore, this is the first-ever study, and the empirical analysis of the study discovered that identified practices are providing valuable insights for manufacturing industries which will be on board on this voyage including institutions, practitioners and other sectors.

The application of lean and quality improvement methods is very common in process improvement projects at organisational levels. The purpose of this research is to assess the adoption of Lean Six Sigma™ approaches for addressing a complex process-related issue in the coal industry.

The sticky coal problem was investigated from the perspective of process-related issues. Issues were addressed using a blended Lean value stream of supply chain interfaces and waste minimisation through the Six Sigma™ DMAIC problem-solving approach, taking into consideration cross-organisational processes.

It was found that the tendency to “solve the problem” at the receiving location without communication to the upstream was, and is still, a common practice that led to the main problem of downstream issues. The application of DMAIC Six Sigma™ helped to address the broader problem. The overall operations were improved significantly, showing the reduction of sticky coal/wagon hang-up in the downstream coal handling terminal.

The Lean Six Sigma approaches were adopted using DMAIC across cross-organisational supply chain processes. However, blending Lean and Six Sigma methods needs to be empirically tested across other sectors.

The proposed methodology, using a framework of Lean Six Sigma approaches, could be used to guide practitioners in addressing similar complex and recurring issues in the manufacturing sector.

This research introduces a novel approach to process analysis, selection and contextualised improvement using a combination of Lean Six Sigma™ tools, techniques and methodologies sustained within a supply chain with certified ISO 9001 quality management systems.

This article examines the direct effect of total quality management (TQM) practices on organizational performance (OP) and innovation (INN), as well as their indirect effect through organizational learning (OL) as a mediating variable. In addition, this survey examines company size as a contextual variable in the relationship between TQM and outcome variables.

A conceptual framework is proposed to test causal links between TQM, OP, INN and OL. To empirically test this framework, 110 questionnaires were collected from large Tunisian quality-certified industries, and 167 questionnaires were collected from small and medium-sized industries (SMIs) in order to examine the effect of company size. In this order, a multigroup analysis (MGA) is performed.

Using the structural equation modeling technique, seven hypotheses are investigated. The results reveal that TQM has a direct and significant positive effect on OP and INN. Data analysis shows that there is a significant positive effect between TQM and OL, while OL positively influences OP and INN. Furthermore, the results illustrate a mediating effect of OL between TQM and OP and INN. The results reveal that large industries and SMIs show significant differences in the relationship, including the conceptual model.

The conceptual framework can be used by practitioners for effective implementation of TQM practices to simultaneously improve operational performance, quality performance and INN. This study also focuses on the role of OL in large-scale industries.

While the relationships between TQM, INN and OP have been examined separately in previous studies, this study examines the relationship between these variables in a unique model in Tunisian industries, including OL as a mediating variable. In addition, it is one of the few studies that considers firm size as a contextual variable and provides an analysis of its effect on the relationships between these variables. This study presents new data and empirical insights into the relationship between these variables.

This study aims to explore the synergetic effects of total quality management and supply chain management (TQM–SCM) initiatives and their effects on organizational performance (OP). This research has been conducted in Pakistan’s logistics sector. The research reveals the synergistic effect of TQM and SCM initiatives and their effects on OP.

The constructs of the TQM and SCM were chosen after reviewing the literature that was critical for the logistics sector. The synergetic effect of TQM–SCM on OP has been evaluated. The mediating, direct and indirect effects were also evaluated in different models independently. Structural equation modelling was applied to drive the results via using AMOS.

It was observed during the analysis that both the TQM and SCM have a significant effect on OP. Both TQM initiatives have directly correlated to the improvement in SCM, and both have a positive effect on an organization. This research study has aided logistics firms that are focusing on TQM and SCM planning and implementation. The results can give management a better and more in-depth knowledge of the TQM initiatives and OP.

The data was collected through email and personal visits from different organizations. The data was collected through an adopted questionnaire. It is found in the study that many people at the managerial level have limited knowledge regarding SCM and TQM. The results may vary if the knowledge of the employees is improved.

The current study presents an upscale addition by examining the function of SCM and TQM linkage in OP as well as their relationship. The evaluated model serves as a guideline for firms looking to expand and achieve maximal OP.

Text.

The evaluated model is developed in this study that serves as a guideline for firms looking to expand a new method to reach maximum OP.

The purpose of the article is to examine the concepts of knowledge management strategies, innovation and service quality in information technology companies that have research and development (R&D) departments in the technoparks of research universities.

The research was carried out in information technology companies with R&D departments in the technoparks of universities. Due to the “innovation” focus of the research, 302 engineers were selected by random sampling from engineers working in information technology companies in technoparks, and the prepared scale was sent to them via e-mail. In total, 302 units of data were subjected to path analysis and mediation effect analysis using the SmartPLS program.

In the research, it is supported by hypotheses that both knowledge management strategies and organizational innovation have a positive effect on the success of service quality and product innovation in information technology companies with R&D departments. At the same time, it can be explained as a result of analysis that innovation capability has both an independent and an intermediary variable effect.

Considering the limitations of the research, it is not correct to generalize the results of the analysis because the research was conducted only in information technology companies located in technoparks, and the data were collected from engineers working in these companies. For this reason, it is recommended that similar studies that are planned to be conducted in the future should do their research by taking this situation into account. At the same time, it is recommended to carry out future studies in different sectors and to bring the results obtained to the literature by comparing them.

The importance of information is increasing in technology-oriented companies where competition is increasing. Companies that cannot go beyond imitation or offer similar products and/or services cannot compete with their competitors in a competitive environment. The fact that companies can be successful in a competitive environment is supported by hypotheses as a result of the analysis that they need to develop organizational innovation and knowledge, as well as develop innovation capability at the same time.

The research is an original study in terms of examining the R&D departments of information technology companies operating in the technoparks of universities. Innovation and knowledge management strategies are examined within the scope of the research model by collecting data from information technology companies with R&D departments.