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The purpose of this paper is to explore the evidence of interlinkages between Lean and sustainability among organisational leaders in the early stages of Lean implementation.

A multiple-site case study was conducted to study the connections between Lean and sustainable development during the implementation stages of a Lean practice. In-depth interviews were conducted with managers about their knowledge and understanding of the interlinkages between Lean and sustainable development. The findings were then used as an analytic frame to determine whether these interlinkages were present in the organisation.

Evidence of interlinkages between Lean and sustainable development was found; however, their presence was incomplete and inconsistent across clinics.

Insights from the research can help organisations plan for the implementation of Lean practice, particularly when a sub-goal is to achieve sustainable development.

The study shows the importance of focussing on managers’ knowledge and understanding of the interlinkages between Lean and sustainable development when implementing Lean in order to utilise Lean’s full potential to achieve sustainability.

This study aims to scrutinize time-varying return and volatility interlinkages among major cryptocurrencies, NFT tokens and DeFi assets between 1 July 2018 and 19 February 2023 and determine optimal portfolio allocations and hedging effectiveness under different portfolio construction techniques.

This work examines time-varying return and volatility interlinkages among major cryptocurrencies, NFT tokens, and DeFi assets between 1 July 2018 and 19 February 2023. To this end, the time-varying parameter-vector autoregression (TVP-VAR)-based connectedness methodology of Antonakakis et al. (2020) This approach is an extended version of the Diebold–Yilmaz (DY) method (Diebold and Yılmaz, 2014) and has advantages over the original DY. First, unlike the DY, it is free of the selection of a particular window size. Second, it has robustness for the outliers. Furthermore, following Broadstock et al. (2022), the author estimates time-varying optimal portfolio weights and hedging effectiveness under different portfolio construction scenarios.

This study's results indicate the following results: (1) The overall connectedness indices prominently capture well-known financial/geopolitical distress incidents; (2) the leading cryptocurrencies (ETH, BTC and BNB) are the largest transmitter of return shocks, while LINK and BTC are the largest transmitters/recipients of volatility shocks; (3) cryptocurrencies, NFTs and DeFi form distinct cluster groups in terms of return and volatility connectedness; (4) the connectedness networks estimated around the 2022 cryptocurrency crash and the FTX's filing for the bankruptcy are characterized by the strongest return and volatility interlinkages; (5) optimal portfolio strategies computed by different portfolio construction techniques display similar motifs and have sustained growth paths except for some short-lived drop backs.

This study's findings imply several policy suggestions for investors, stakeholders and policymakers. First, the study's time-based dynamic interlinkages can help market participants in their optimal portfolio decisions. In particular, the persistent net receiving roles of the DeFi assets and the NFTs throughout the episode, especially around the financial/geopolitical turmoil, underpin their safe haven potentials (Umar et al., 2022a, b). Finally, since the total connectedness indices (TCIs) are prone to significantly increase around financial/geopolitical burst times, these tools can be valuable for policy makers to monitor risk.

The contribution of knowledge is at least threefold. First, the author focuses on the dynamic time interlinkages among major cryptocurrencies, NFTs and DeFi assets in July 2018 and February 2023 considering the prominent recent financial/geopolitical incidents. Second, the author estimates network topologies of dynamic connectedness around financial/geopolitical bursts and compared them in terms of interlinkages. Finally, the author calculates the time-varying optimal portfolio allocations and hedging effectiveness under different portfolio construction techniques.

The authors attempt to explore fat tails and network interlinkages of oil prices and the six largest cryptocurrencies from 1st January 2018 and 1st August 2021. The authors also investigate the influences of the COVID-19 pandemic on these network interlinkages.

The authors follow Diebold and Yilmaz (2012) to calculate the spillover index the dynamic correlation coefficient model firstly employed by Engle (2002) to study how the volatility of oil prices are transmitted to those of cryptocurrency return and liquidity and vice versa.

The results confirm the presence of time-varying interlinkages between the volatilities of the oil market and the cryptocurrency market. Notably, uncertain events like the COVID-19 health crisis significantly influence the time-varying interlinkages they augment dramatically during the COVID-19 health crisis. The turbulence of the cryptocurrency market, especially from Bitcoin and Ethereum, significantly impacts those of the oil market. The role of the oil market in transmitting the effect of respective shocks to the cryptocurrency market, on the other hand, is time-varying, which is only reported when the COVID-19 pandemic first appeared at the beginning of 2020. The turbulence of the cryptocurrency market in the system is greatly explained by themself rather than a transmission mechanism of shocks to the oil market.

Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets.

The most significant benefit of the approach is how simple it is to calculate net pairwise connectivity, which identifies transmission channels between these commodity and financial markets. The authors are also the first to use the quasi-maximum likelihood (QML) estimator to estimate the DCC model to measure the volatility spillover index to reflect the level of interdependence between the different markets. By using a daily and up to date database, the authors can observe the role of each market in transmitting and receiving the shocks between two different sub-periods: (1) before and (2) during the COVID-19 pandemic crisis.

Lecture recording provides learning material for local and distance education. The TeleTeachingTool uses the very flexible screen recording technique to capture virtually any material displayed during a presentation. With its built‐in annotation system teachers can add freehand notes and emphasize important parts. Unlike other screen recorders, our implementation offers slide‐based navigation, full text search and annotated scripts, which are obtained by automated post‐production. This article presents how automated analysis generates indices for slide‐based navigation on the fly and how to achieve live interlinkage of annotations with slides so that annotations disappear when a slide is changed and are made visible again when returning to that slide later during presentation, although screen recorders generally do not provide an association of annotations with slides.

The purpose of this paper is to study the interlinkages between the cryptocurrency and stock market by characterizing their connectedness starting from January 1, 2018 to December 31, 2021.

The author employs a time-varying parameter vector autoregression (TVP-VAR) in combination with an extended joint connectedness approach.

The pandemic shocks appear to have influences on the system-wide dynamic connectedness, which reaches a peak during the COVID-19 pandemic. Net total directional connectedness suggests that each cryptocurrency and stock have a heterogeneous role, conditional on their internal characteristics and external shocks. In particular, Bitcoin and Binance Coin are reported as the net receiver of shocks, while the role of Ethereum shifts from receivers to transmitters. As for the stock market, the US stock market stays persistent as net transmitters of shocks, while the Asian stock market (including Hong Kong and Shanghai) are the two consistent net receivers. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the impact most severe at the beginning of 2020.

Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets.

The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages among these two markets. The author employs the TVP-VAR combined with an extended joint connectedness approach.

Examines critically traditional economic paradigms as well as those given by Hayek and Buchanan on markets with constitutional contracts in order to contrast them with yet another view of market ‐ that endogeneity of various political and economic processes creates a global system of interlinkages among and between policy variables and socio‐economic variables. By invoking the methodology and epistemology of such a system develops a theory of globally interactive market processes. In such a globally interactive system, markets are seen to be induced by and to regenerate circularly endogenous preferences. Knowledge induction becomes epistemologically critical in such an evolutionary and interactive order. Hence, these globally knowledge‐induced interlinkages generated by policy‐market interactions are made to establish and explain what is termed here as a system of social contracts.

The European Innovation Scoreboard is an important indicator of innovation performance across European Member States. Despite its wide application, the indicator fails to highlight the interlinkages that exist among innovation measures and focuses primarily on the linear relationship between the individual measures and the predicted outcome. This study aims to address this gap by applying a novel technique, the fuzzy-set qualitative comparative analysis (fsQCA), to shed light on these interlinkages and highlight the complexity of the determinants underlying innovation performance.

The authors adopted a configurational approach based on fsQCA that is implemented on innovation performance data from European Member States for the period 2011–2018. The approach is based on non-linearity and allows for the analysis of interlinkages based on equifinality, that is, the model recognises that there are different potential paths of high and low innovation performance. In addition, the approach allows for asymmetric relations, where a low innovation outcome is not the exact inverse of that which leads to high innovation outcome.

The results clearly indicate that innovation outcomes are not based on simple linear relations. Thus, to reap the desired effects from investments in innovation inputs, the complex set of indicators on which innovation performance is based should be taken into consideration. The results clearly indicate the elements of equifinality and asymmetric relations. Different paths lead to high innovation performance and low innovation performance.

The method applied to investigate the determinants of innovation performance is the prime original factor of this study. Thus, the study contributes to literature by highlighting the complexity involved in understanding innovation. By recognising and attempting to detangle this complexity, this study will assist not just academics but also policymakers in designing the necessary measures required to reach this important outcome for a country’s competitive edge.

This chapter explores Food for Change, a social entrepreneurial program created by the Houston Food Bank. Food for Change explicitly considers the interlinkages of social problems within an individual. Food for Change collaborates with educational and training organizations and healthcare providers to use supplemental food resources to address clients' needs antecedent to food insecurity. We propose a model to conceptualize how food insecurity is influenced by multiple levels of social determinants. We then describe the Food for Change program and offer lessons about the holistic nature of clients, the productivity and challenges of interorganizational collaborations to address the roots of social problems, and the forethought and courage of organizational leadership to try to create self-sufficient clients who might become liberated from their services.

Most scholars in public administration and management research would agree that there is a connection between the culture of a nation or region and the way management in public administration is structured and working (“public management arrangements”). However, to be incorporated into public management research and theory, a more precise notion about the forms, ways, and mechanisms of the interlinkage between societal culture and public management is required. A look into public management literature reveals that wide use and reference is made to the importance and influence of culture on public management arrangements – mostly, though, using the term “culture” as a shortcut for “organizational culture”. Public management treatises stress the influence of past events and contexts for the specific functioning and establishment of organizations, rules, and perceptions which in turn have great influence on the reception and functioning of public management mechanisms (Heady, 1996; Jann, 1983; Schröter, 2000; Pollitt & Bouckaert, 2004). Elsewise, organizational culture – or more precisely change thereof – is claimed to be the result of public management efforts (Ridley, 2000; Schedler & Proeller, 2000). In sum, the interlinkage between culture and public management is there, but is not systematically and explicitly incorporated by referring to adequate theory. Although cultural theory has gained considerable attention (Hood, 1998), there are still other concepts for the analysis of cultural facts that may be of interest to the subject, too.

This paper aims to study the interlinkages between cryptocurrency and the stock market by characterizing their connectedness and the effects of the COVID-19 crisis on their relations.

The author employs a quantile vector autoregression (QVAR) to identify the connectedness of nine indicators from January 1, 2018, to December 31, 2021, in an effort to examine the relationships between cryptocurrency and stock markets.

The results demonstrate that the pandemic shocks appear to have influences on the system-wide dynamic connectedness. Dynamic net total directional connectedness implies that Bitcoin (BTC) is a net short-duration shock transmitter during the sample. BTC is a long-duration net receiver of shocks during the 2018–2020 period and turns into a long-duration net transmitter of shocks in late 2021. Ethereum is a net shock transmitter in both durations. Binance turns into a net short-duration shock transmitter during the COVID-19 outbreak before receiving net shocks in 2021. The stock market in different areas plays various roles in the short run and long run. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the most severe impact at the beginning of 2020.

Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets.

The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages between these two markets.

本學術論文擬透過找出加密貨幣與股票市場兩者相互關聯之特徵,來探討這個聯繫;文章亦擬探究2019冠狀病毒病全球大流行對這相互關聯的影響。

作者以分量向量自我迴歸法、來找出2018年1月1日至2021年12月31日期間九個指標的關聯,藉此探討加密貨幣與股票市場之間的關係。

研究結果顯示,全球大流行的驚愕,似對全系統動態關聯產生了影響。動態總淨值定向關聯暗示了就我們的樣本而言,比特幣是一個純短期衝擊發送器。比特幣在2018年至 2020年期間是一個衝擊的長期純接收器,並進而於2021年年底成為一個衝擊的長期純發送器。以太坊則為短期以及長期之純衝擊發送器。幣安在2019冠狀病毒病爆發期間,在2021年接收純衝擊前、成為一個純短期衝擊發送器。位於不同地區的股票市場,無論在短期抑或長期而言均扮演各種不同的角色。在2019冠狀病毒病全球大流行的驚愕期間,成對的關聯顯示了加密貨幣可以以2020年年初最嚴重的影響去解釋和說明股票市場的波動。

研究結果使我們能深入認識有關的市場之間不同情緒和看法的蔓延所帶來的影響的主要先例,這些知識、亦能幫助決策者制定適當的政策,以減少有關的市場的弱點,並把這些市場間的風險和不確定性的散播減到最低。

作者是首位研究加密貨幣與股票市場之間的相互關聯的學者,亦是首位學者、去評估像2019冠狀病毒病健康危機的不確定事件,會如何影響有關的兩個市場之間的動態相互關聯。