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Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.

Interruptions are prevalent in knowledge work, and their negative consequences have driven research to find ways for interruption management. However, these means almost always leave the responsibility and burden of interruptions with individual knowledge workers. System-level approaches for interruption management, on the other hand, have the potential to reduce the burden on employees. This paper’s objective is to pave way for system-level interruption management by showing that data about factual characteristics of work can be used to identify interrupting situations.

The authors provide a demonstration of using trace data from information and communications technology (ICT)-systems and machine learning to identify interrupting situations. They conduct a “simulation” of automated data collection by asking employees of two companies to provide information concerning situations and interruptions through weekly reports. They obtain information regarding four organizational elements: task, people, technology and structure, and employ classification trees to show that this data can be used to identify situations across which the level of interruptions differs.

The authors show that it is possible to identifying interrupting situations from trace data. During the eight-week observation period in Company A they identified seven and in Company B four different situations each having a different probability of occurrence of interruptions.

The authors extend employee-level interruption management to the system-level by using “task” as a bridging concept. Task is a core concept in both traditional interruption research and Leavitt's 1965 socio-technical model which allows us to connect other organizational elements (people, structure and technology) to interruptions.

The purpose of this paper is to explore the internal interaction mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth from a systematic perspective, based on which this work forecasts their future development trends.

In this study, a multivariate grey model is applied to the prediction of marine scientific research and education, industrial structure upgrading and marine economic growth. Considering the impact of the COVID-19 on marine development, this paper introduces the weakening buffer operator into MGM(1,m) and constructs the AWBO-MGM(1,m) model. To verify the validity and accuracy of the new model, this paper uses AWBO-MGM(1,m), MGM(1,m), GM(1,N), GM(1,1), back propagation neural network and linear regression models for simulation and prediction based on the data from 2010 to 2021, respectively.

From the theoretical perspective, the development of marine scientific research and education can accelerate industrial upgrading and promote marine economic growth by providing high-quality talents, promoting marine science and technology progress and reducing transaction costs; while the upgrading of marine industrial structure and marine economic growth can promote the development of marine scientific research and education by guiding social capital, enhancing talent demand and stimulating market vitality. From the empirical analysis, the AWBO-MGM(1,m) model can effectively deal with epidemic shocks and has higher fitting and prediction accuracy than the other five comparative models.

The government should pay attention to the construction of marine scientific research and education, so as to provide high-quality talents and advanced scientific research results for the high-quality development of marine economy. On the basis of using science and technology to firmly build the primary and secondary marine industries, the government should actively guide the labor, capital and other factors of production to the tertiary industry, thereby promoting the optimization and upgrading of marine industrial structure.

On the one hand, the interplay mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth is analyzed from a systematic perspective; on the other hand, the enhanced AWBO-MGM(1,m) possesses higher forecasting performance and is applicable to the systemic multivariate forecasting problem in the presence of outstanding external shocks.

This study aims to set out to identify and evaluate potential obstacles to successfully implementing lean construction (LC) as a result.

Several indicators were recognized as major obstacles following an exhaustive assessment of the literature and a multicriteria decision analysis based on the analytic hierarchy process (AHP) of information obtained from a questionnaire survey that was directed to practitioners in the Indian construction industry.

The results of this AHP model suggest that “Managerial” and “Inadequate resources” categories with a priority weight of “0.361” and “0.309” have the highest levels of influence, respectively, while “Inadequate knowledge” and “just in time (JIT)” categories with a priority weight of “0.053” and “0.034” have the lowest levels of influence, respectively.

Construction companies can use the study’s findings as a guide to determine whether they are ready to embrace LC, learn more about the components needed for implementation or investigate any challenges that may arise. These businesses can then create plans to promote the adoption and application of the lean philosophy.

The Indian construction industry may see great success with LC management initiatives. LC concepts have been adopted by many nations, but during the past 20 years, there has only appeared to be a limited amount of lean implementation in the Indian construction industry. It seems that several structural and cultural barriers are preventing its effective implementation. Organizations will not be able to determine what improvement efforts are required, where these efforts should be directed or which initiatives could provide the best outcomes if they are unaware of the elements that influence the effective implementation of LC.

The purpose of this paper is to know which growth-impeding constraints are perceived to act upon operations of small- to medium-sized (SME) companies by their owner-managers and to recommend transitionary paths to elevate constraints and increase contribution levels made by SMEs’ operations. To do so, this research has been primarily founded upon Hayes et al.’s (2005) operations contribution model for differentiating between different levels of operations’ contribution, and secondarily on the theory of constraints philosophy to explain the perceptions of constraints found at each level – current and future.

An open-ended survey and a series of group workshops have gathered new empirical data about these perceptions, which were coded using the relational content analysis to identify a parsimonious set of perceptual growth-impeding constraint categories. The most popular transitions were identified and a correlation of frequency rank orders between “perceived current” and “perceived future” constraints categories was calculated, and likely transitionary paths for growth are discussed. Three SME case studies were documented in related action research to contextualise survey findings.

The most popular transition was from “neutral” to “leading”. A lack of people capability was perceived to be the most commonly reported growth-impeding constraint category, followed by a combined lack of process competence and product and service innovation, further followed by a lack of skills in information technology automation. In addition, a new conceptual model has been generated inductively to address shortcomings found in the original operations contribution model (Hayes et al., 2005) during its application to UK SMEs. The new model is referred to in this paper as the “Operations Growth Rocket”.

This research only used data from UK SMEs.

This work should help SME owner-managers to overcome growth-impeding constraints that act upon their operations and assist them to develop more effective actions and paths to increase the contribution levels made by their operations. This in turn should support growth of their organisations. Findings will also inform teaching about more effective operations management in SMEs.

This work should help UK SMEs to grow, which in turn will strengthen the UK economy.

A novel approach and new data from 208 SMEs modify a classical operations contribution model (Hayes et al., 2005). This is achieved by considering transitionary paths to be meta-categories continua abstracted from constraint categories combined with case data for moving towards higher levels of operations contribution, rather than using discrete growth-impeding and growth-constraining “levels”. This research has inductively generated a new version of the classical contribution model that should be more suitable for stimulating growth in (UK) SMEs.

The purpose of this paper is to investigate how a substantial organization gradually builds a management accounting system from scratch, changing its accounting routines by learning processes. The paper uses the experiential learning theory and the concept of learning style to investigate the learning process during management accounting change. The study aims to expand the domain of management accounting change theory to emphasize the learning-related aspects that can constitute it.

The paper provides an interpretation of management accounting change based on the model of problem management proposed by Kolb (1983) and the theory of experiential learning (Kolb, 1976, 1984). The study is based on a 14-year longitudinal case study (1994‐2007). The case examined can be considered a theory illustration case. Data were obtained from a broad variety of sources including interviews, document analysis and adopting an interventionist approach during the redesign of the costing system.

The paper contributes to two important aspects of management accounting change. First, it becomes apparent that the costing information change was not a discrete event but a process of experience and learning conducted through several iterations of trial-and-error loops that extended over the years. Second, the findings reveal that the learning process can alter management accounting system design in a radical or incremental way according to the learning style of the people involved in the process of change.

Because of the adopted research approach, results could be extended only to other organizations presenting similar characteristics. Several further areas of research are suggested by the findings of this paper. In particular, it would be of interest to investigate the links between learning styles and communication and its effect on management accounting change.

The paper includes implications for the management of learning during management accounting change, to improve the efficiency and effectiveness of this process.

This paper is one response to the call for an interdisciplinary research approach to the management accounting change phenomena using a “method theory” taken from the discipline of management to provide an explanation of the change in management accounting. In respect of the previous literature, it provides two main contributions, namely, the proposal of a model useful both to interpret and manage learning processes; the effect of learning style on management accounting routines change.

This study aims to propose and evaluate a novel framework of strategic adaptability in dyadic negotiations. The authors define strategic adaptability as a reaction to a cue that leads to shifts between integrative and distributive strategies. Based on the literature on turning points, phase models and strategic negotiations, the authors developed an initial framework identifying five distinct strategic adaptations.

To verify the framework, the authors analyzed two negotiation simulations with a diverse set of negotiation students. Negotiations were content-coded, and adaptations were labeled.

The authors found a consistent pattern across two studies. Overall, 12% (study 1) and 18% (study 2) of all speaking turns were identified as strategic adaptations. The findings empirically confirmed four of their strategic adaptation types: adapt to deadlock, follow adaptation by opponent, adapt to priority of issue under discussion and adapt to new information on issue. Moreover, findings of this study revealed two new types of strategic adaptability: delayed adaptation to opponent and adapt to understand opponent. Study 2 additionally revealed that strategies vary with the negotiation phase, and negotiation outcome seems to benefit more from the constellation rather than the frequency of adaptations. Furthermore, lower-scoring negotiators tended to adapt to the opponent’s strategy instead of initiating a change in strategy.

The findings of this study provide preliminary insights into how strategic adaptations unfold. These findings present future research opportunities to further test the framework's robustness, increase the knowledge of individual and cultural factors, explore the relationship with negotiation outcomes and develop educational interventions to enhance strategic adaptability.

This paper aims to explore and analyse stakeholders’ perceptions of the development priorities and suggests more effective strategies to assist sustainable economic growth in the United Arab Emirates (UAE).

The authors use the World Bank data set, which collects various stakeholders’ opinions on the UAE development. First, the exploratory factor analysis has been applied to detect the main groups of development priorities. Second, the fuzzy cluster analysis has been conducted to detect the groups of stakeholders with different attitudes towards the importance of extracted groups of priorities. Third, clusters have been compared according to demographics, media usage and shared prosperity goals.

The two main groups of development priorities have been extracted by the exploratory factor analysis: economic priorities and sustainability priorities. Four clusters have been detected according to the level of motivation when it comes to the economic and sustainability priorities: Cluster 1 (High economic – High sustainability), Cluster 2 (High economic – Medium sustainability), Cluster 3 (High economic – Low sustainability) and Cluster 4 (Low economic – Low sustainability). Members of the cluster that prefer a high level of economic and sustainability priorities (Cluster 1) also prefer more diversified economic growth providing better employment opportunities and better education and training for young people in the UAE.

Limitations stem from the survey being conducted on a relatively small sample using the data collected by the World Bank; however, this data set allowed a comparison of various stakeholders. Future research should consider a broader sample approach, e.g. exploring and comparing all of the Gulf Cooperation Council (GCC) countries; investigating the opinions of the expatriate managers living in the UAE that are not from GCC countries; and/or including other various groups that are lagging, such as female entrepreneurs.

Several practical implications were identified regarding education and media coverage. Since respondents prioritize the economic development factors over sustainability factors, a media campaign could be developed and executed to increase sustainability awareness. A campaign could target especially male citizens since the analysis indicates that males are more likely to affirm high economic and low sustainability priorities than females. There is no need for further diversification of media campaigns according to age since the analysis did not reveal relevant differences in age groups, implying there is no inter-generational gap between respondents.

This paper contributes to the literature by comparing the perceived importance of various development goals in the UAE, such as development priorities and shared prosperity indicators. The fuzzy cluster analysis has been used as a novel approach to detect the relevant groups of stakeholders in the UAE and their developmental priorities. The issue of media usage and demographic characteristics in this context has also been discussed.