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Due to the absence of industry and region-specific implementation guides, change efforts, in particular continuous improvement implementations, continue to report high failure rates. The purpose of this paper is, therefore, to present a finalised implementation framework specifically tailored for manufacturing companies.

A conceptual framework derived from the existing literature is validated, through a Delphi study, by an expert panel to review its content and suitability for a practical application.

This paper proposes a finalised framework tailored to the practical needs of users. The results of the Delphi approach offer a phased implementation framework that provides an overview of the implementation process of continuous improvement initiatives and the key activities involved. The framework is suitable for use by both business leaders and continuous improvement practitioners with varying degrees of previous implementation experience.

The research was carried out in the UK and is specifically focused on the manufacturing industry. It is therefore not clear the applicability of the framework presented to other regions and industries. The framework, although validated through several phases of research, still requires practical application and testing.

Business leaders and continuous improvement practitioners will benefit from having the necessary content presented in a manner that will promote its practical application. It has also been demonstrated that the framework is robust in its content, incorporating the literature findings as well as the experience of an expert panel encompassing 20 people.

This research fills a gap in process science by defining and explaining entropy and the increase of entropy in processes.

This is a theoretical treatment that begins with a conceptual understanding of entropy in thermodynamics and information theory and extends it to the study of degradation and improvement in a transformation process.

A transformation process with three inputs: demand volume, throughput and product design, utilizes a system composed of processors, stores, configuration, human actors, stored data and controllers to provide a product. Elements of the system are aligned with the inputs and each other with a purpose to raise standard of living. Lack of alignment is entropy. Primary causes of increased entropy are changes in inputs and disordering of the system components. Secondary causes result from changes made to cope with the primary causes. Improvement and innovation reduce entropy by providing better alignments and new ways of aligning resources.

This is the first detailed theoretical treatment of entropy in a process science context.

As media texts, advertisements use representation practices to construct ideological meanings. This study traced the representation of the worker in advertisements with the help of content and thematic analysis. The study aimed to reveal the representation of the worker in the advertisements and to make the representations of the worker built through advertisements visible. The study was limited to ads that received an Effie Award in Turkey in 2020 and 2021. In the 2020 Effie Awards, 73 awards were given in 41 categories and in the 2021 Effie Awards, 68 awards were given in 42 categories. Content analysis was applied to 24 advertisements in 2020 and 31 advertisements in 2021. The quantitative data helped to determine the themes in the thematic analysis. Thematic analysis was carried out by regarding the worker as the (in)visible, the (un)voiced, and the bypassed. This study, which reveals that the worker is represented in advertisements through being invisible, unvoiced, and bypassed, claims that the labor of the worker in the production process is ignored through representation practices. In this context, it can be said that the worker is erased and omitted in TV ads on a symbolic level.

The purpose of this paper is to contribute to the growing body of research literature on case clearance levels. Through a social artifact framework, the authors seek to understand the role that documentation of key solvability factors in investigative reports plays in shaping case clearance outcomes.

For this study, 166 non-fatal shooting investigative case files were obtained from a local mid-sized urban police department and coded to assess whether investigators identified key solvability characteristics for non-fatal shooting incidents. Using a logistic regression, the authors assessed the extent that investigative characteristics mentioned in case files were associated with the odds that the case was cleared by arrest.

The findings from this study indicate that investigative case files as a data source are exceedingly unreliable. Investigators do not consistently document investigative practices and intelligence. And those that are consistently documented are a part of institutionalized practices that are unique to their corresponding police department.

This study is original in that it uses a social artifact framework to sharpen the focus on the role that the effective documentation of critical evidence plays in leading to arrests in gun violence cases.

This study theoretically investigates the extant literature published about circular economy and sustainable development to identify significant research themes, the most relevant authors, countries and journals.

Bibliometric analysis is used, followed by cluster formation using co-citation analysis. The clusters are discussed in-depth to identify emerging themes and future research areas.

By systematically reviewing 596 research articles, significant themes of research in this field were found. These include frameworks and indicators to define and assess the circular economy, circular business models and use cases, global and industrial contexts of application of circular economy and different dimensions of the circular economy.

Publications from only one database have been used. Only articles published in relevant academic journals have been used for the bibliometric analysis. For co-citation analysis and cluster formation, only articles with a high number of citations were selected.

The analysis of the various clusters revealed research areas that can be explored in future research to understand the circular economy better and implement its practices to attain sustainability.

This paper aims to better understand how business model innovation (BMI) occurs in the context of sustainable entrepreneurship, emphasizing the dialectical nature of entrepreneurial relationships. To do so, key interdependencies and reciprocal influences between internal/firm-specific and external/environmental factors underlying BMI for sustainability are analysed through co-evolutionary lenses.

A co-evolutionary framework is developed and applied to a longitudinal business model (BM) analysis of 15 Italian widespread hotels, which creatively use historic villages at risk of abandonment to establish their hotels.

Largely influenced by the interplay between internal and external factors, BMI of widespread hotels occurs through multilevel co-adaptations, which are recognised as virtuous by all stakeholders involved. Effective variations of the BM value elements are selected resulting in circular economy practices, which are retained for successful BMI, radical (first) and incremental (thereafter). Knowledge of specific local and multi-local conditions, time awareness and a future-oriented temporal perspective, by both entrepreneurs and policymakers, favour this dynamic.

Developing targeted policies and practices based on increased organisational knowledge supported by indicators can help in selecting and retaining successful variations of BMs appropriately in/with time with positive effects on firms' performance and sustainable development.

This study provides a novel co-evolutionary framework that explicitly links sustainable entrepreneurship and BM concepts in the accommodation sector. It further proposes a dynamic and holistic explanation of BMI for sustainability from which the crucial roles of the time-knowledge binomial and circular practices emerge.

Considering the role of the textile industry in the generation of employment and export in the Indian economy, it is important to comprehend the efficiency level in the operations of the textile units located in different states in India. In this light, the purpose of this paper is to examine the operational efficiency of textile manufacturing units in Haryana, a northern state of India.

The study applies data envelopment analysis (DEA) approach consisting of input-oriented CCR and BCC techniques along with the return to scale technique for the analysis of five years of data from 2015–2016 to 2019–2020.

The results reveal that Haryana’s textile units have significantly underperformed operationally, with an average technical efficiency score of just 0.25 for five years, from 2015–2016 to 2019–2020. The yearly ratings of the overall technical efficiency of the selected textile companies include 0.20, 0.18, 0.18, 0.40 and 0.28; PTE scores are 0.43, 0.43, 0.55, 0.60, 0.62 and scale efficiency scores 0.54, 0.44, 0.29, 0.71, 0.38, respectively, from 2015–2016 to 2019–2020. On the other hand, average of 5.8 units are functioning at the constant return to scale, 10.2 units are at increasing return to scale and average of 45 units are functioning at decreasing return to scale (DRS). It is found that most of the companies are functioning at a DRS; to boost efficiency, these companies must reduce their input size since they are running at a DRS.

The results of the current paper provide key insight into the inefficiency level of the textile manufacturing industry in the context of northern India. Industry professionals can take corrective measures based on these findings. Moreover, for investors and portfolio managers, knowing which companies are efficient and which are not will help them make better decisions. The study helps policymakers to frame appropriate policy guidelines to make the textile units in the state more efficient and competitive.

To the best of the authors’ knowledge, no study has been done so far on the operational performance of the textile industry in Haryana based on the DEA technique. So, it will contribute to the extant literature on the performance of the textile industry.

Internal control systems are critical to an organization's efficiency and promotes the adherence to norms and rules. The purpose of this study is to evaluate the impact of internal control systems on banking industry effectiveness.

Data were collected from 15 commercial and 20 rural banks. The hypothesized relationships were supported by the data. A structural equation modeling was applied in testing the conceptual model and hypothesis. Confirmatory factor analysis was conducted to establish validity and reliability of the dimensions.

The results show that organizational effectiveness was significantly impacted by three dimensions of internal control systems: control activities, control environments and risk assessment. However, the impact of monitoring of control on organizational effectiveness was not significant. The results also show a nonsignificant impact of information and communication on organizational effectiveness.

Since the current study concentrated on the banking sector with its distinct characteristics, the generalizability of the conclusions may be limited.

The study's findings may aid decision-makers and stakeholders in the adoption, designing and implementation of proactive internal control system to enhance operational efficiency, effectiveness and competitive advantage.

The study advances the literature by empirically evidencing that internal control systems impact organizational effectiveness.

The objective of this work is to identify the strategies of digitalization embraced by the European Capitals of Culture 2020 (ECoC) in replying to the limitations due to COVID-19 emergence and to understand how DT have impacted in terms of resilience and innovation. This study aims to provide a contribution at the understanding of the effects and benefits of the digitalization in supporting the reorganization of the cultural projects of ECoC 2020 in replying to the COVID-19.

This paper is based on an exploratory multiple case study methodology. As a suitable investigative tool for the analysis of a contemporary phenomenon in their natural settings, case study methodology allows to integrate evidences resulting from multiple sources (Yin, 2006, 2008; Eisenhardt, 1989). Data collection, monitoring and analysis rely on the combination of Web-based desk analysis and social big data analytics. The integration of such sources has been addressed towards the investigation of the strategies of digitalization undertaken by the two ECoC cities, Galway in Ireland and Rijeka in Croatia, respectively.

Evidences in terms re-organization of the cultural projects, digitalization of the tourist experiences, commitment of local communities and visitors have been derived from the study while the cross comparison of the two cases has allowed to identify common and specific patterns.

The paper presents some limitations. Firstly, the methodological approach as well as the nature of data collected suggest the need of future investigation with the inclusion of a larger sample of ECoCs and the inclusions of quantitative date related to trends of online cultural experiences and travel data. Secondly, the theoretical perspective of digitalization used in this study can be accompanied by other perspectives such as innovation and resilience capabilities of an ECoC.

This study contributes to the academic literature by providing a better understanding of the level of resilience generated vis-à-vis the COVID-19 pandemic and the role of DT in promoting participation in culture and implementing cultural initiatives of ECoCs. However, despite the relevance of the topic, the attention from the academic literature on the topic of digitalization in cultural and creative industries is still limited. Moreover, even more limited is the knowledge about the effects of DT and if their opportunities are actually transformed in positive outcomes.