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The purpose of this manuscript is to detect heart fault using Electrocardiogram. Mutually low and high frequency noises such as electromyography (EMG) and power line interference (PLI) degrades the performance of ECG signals.

The ECG record depicts the procedural electrical movement of the heart, which is non-invasive foot age obtained by placing surface electrodes on designated locations of the patient’s skin. The main concept of this manuscript is to present a novel filtering method to cancel the unwanted noises in ECG signal. Here, intrinsic time scale decomposition (ITD) is introduced to suppress the effect of PLI from ECG signals.

In the existing ITD, the gain control parameter is a constant value; however, in this paper it is an adaptive feature that varies according to certain constraints. Simulation outcomes show that the proposed method effectively reduces the effect of PLI and quantitatively express the effectiveness with different evaluation metrics.

The results found by the proposed method are compared with Fourier decomposition technique and eigen value decomposition methods (EDM) to validate the effectiveness of the proposed method.

The aim of this study is to examine the trend over time of the demand for .it domain names.This study first assesses whether there is a phase of growth and expansion or at a point of saturation. Second, this research can be useful also to compare researches that have considered other internet metrics and other models.

This paper describes the forecasting methods used to analyze the internet diffusion in Italy. The domain names under the country code top-level domain “.it” have used as metrics. To predict domain names .it the seasonal auto regressive integrated moving average (SARIMA) model and the Holt-Winters (H-W) methods have been used.

The results show that, to predict domain names .it the SARIMA model is better than the H-W methods. According to the findings, notwithstanding the forecast of a growth in domain names, the increase is however limited (about 3%), tending to reach a phase of saturation of the market of domain names .it.

In general many authors have studied internet diffusion applying statistical models that follow an S-shaped behavior. On the other hand, the more used diffusion models that follow an S-shape not always provide an adequate description of the Internet growth pattern. To achieve this goal, this paper demonstrates how the time series models, in particular SARIMA model and H-W models, fit well in explaining the spread of the internet.

Democratic renewal in Sri Lanka as well as a cross the Global South depends on strengthening democratic social movements within varieties of patrimonial capitalism. Patrimonial capitalism, emphasising patron–client relations, coincide with weakening democratic institutional cultures and practices. The dominant corruption/anti-corruption narrative is bracketed with elite class strategies aimed at negotiating a ‘managed corruption’. The realm of representative politics creating consent for patrimonial capitalism is shaped by: ethnic and class relations; the weakening of working-class parties; patriarchal cultures within parties; links with criminal networks; opaque finances and the integration of mainstream media with party patronage.

Democratising the realm of representative politics points towards democratic social movements. The internal dynamics of social movements, their relationships with political parties and collective learning are significant factors that shapes the strategic orientation of social movements. State repression of social movements highlights the need for demilitarisation and the abolition of prisons. The global sense of this local struggle relates to transforming financial markets and platform economies towards notions of financial and digital commons. The integration of different realms of politics, such as representative, movement, life and emancipatory politics, is vital for reinforcing solidarity as the basis for counter-hegemonic struggles.

The pandemic had a huge negative impact globally on small and micro firms, particularly on cultural enterprises, making it imperative for them to create strategic solutions for sustainable business models and customer relationships. This chapter studies the digital interventions employed by the micro cultural enterprises in the Japanese Onsens (Hot baths) sector during the pandemic period in Japan. Using the theoretical lenses of service dominant logic and value creation, the study extracts four prominent value creation processes from the analysis of the employed secondary data. The study underlines the importance of collaboration between a firm's internal and external resources, their creative use of operant resources, and a robust customer orientation leading to creative digitalization. The results of the study show how cultural enterprises can rethink customer service in the cultural and creative sector. It also draws attention to the need for more robust policies and support systems that can encourage global cultural enterprises to develop sustainable business models.

This paper aims to explore the implications of algorithmic management on careers and employment relationships in the Nigerian gig economy. Specifically, drawing on labour process theory (LPT), this study provides an understanding of the production relations beyond the “traditional standard” to “nonstandard” forms of employment in a gig economy mediated by digital platforms or digital forms of work, especially on ride-hailing platforms (Uber and Bolt).

This study adopted the interpretive qualitative approach and a semi-structured interview of 49 participants, including 46 platform drivers and 3 platform managers from Uber and Bolt.

This study addresses the theoretical underpinnings of the LPT as it relates to algorithmic management and control in the digital platform economy. The study revealed that, despite the ultra-precarious working conditions and persistent uncertainty in employment relations under algorithmic management, the underlying key factors that motivate workers to engage in digital platform work include higher job flexibility and autonomy, as well as having a source of income. This study captured the human-digital interface and labour processes related to digital platform work in Nigeria. Findings of this study also revealed that algorithmic management enables a transactional exchange between platform providers and drivers, while relational exchanges occur between drivers and customers/passengers. Finally, this study highlighted the perceived impact of algorithmic management on the attitude and performance of workers.

The research presents an interesting case study to investigate the influence of algorithmic management and labour processes on employment relationships in the largest emerging economy in Africa.

Testing business processes is crucial to assess the compliance of business process models with requirements. Automating this task optimizes testing efforts and reduces human error while also providing improvement insights for the business process modeling activity. The primary purposes of this paper are to conduct a literature review of Business Process Model and Notation (BPMN) testing and formal verification and to propose the Business Process Evaluation and Research Framework for Enhancement and Continuous Testing (bPERFECT) framework, which aims to guide business process testing (BPT) research and implementation. Secondary objectives include (1) eliciting the existing types of testing, (2) evaluating their impact on efficiency and (3) assessing the formal verification techniques that complement testing.

The methodology used is based on Kitchenham's (2004) original procedures for conducting systematic literature reviews.

Results of this study indicate that three distinct business process model testing types can be found in the literature: black/gray-box, regression and integration. Testing and verification approaches differ in aspects such as awareness of test data, coverage criteria and auxiliary representations used. However, most solutions pose notable hindrances, such as BPMN element limitations, that lead to limited practicality.

The databases selected in the review protocol may have excluded relevant studies on this topic. More databases and gray literature could also be considered for inclusion in this review.

Three main originality aspects are identified in this study as follows: (1) the classification of process model testing types, (2) the future trends foreseen for BPMN model testing and verification and (3) the bPERFECT framework for testing business processes.

The Rajapaksa regime over the 2005–2022 period promoted a national-popular project based on a militarised Sinhala-Buddhist nationalism promoting a market-driven rentier economy. It illustrated a form of patrimonial capitalism undermining public accountability and the efficacy of the state bureaucracy. This popular-national project was dependent on strengthening ties with China while distancing relations with India and the Global North (USA and the EU). The ways in which the external relations were coordinated reinforced discrimination against Tamil and Muslim communities, while disregarding their demands for justice and reparations. The increasing integration of the economy with financial markets, driven by the Central Bank, amplified the commercialisation of the state, restraining public revenues and state oversight. Meanwhile, the militarisation of the state involved the commercialisation of the military, opaque military budgets and violent repression of protests. The Rajapaksa regime, which enabled a minority-privileged (leisure) class to culturally flourish in regulated safe spaces, also instigated multiple protests from below demanding democracy as well as justice.

Manufacturing in Mauritius is mostly export-oriented. Any supply chain (SC) failure or resilience deficit may result in cancellation of orders and loss of customers, market share and revenue and reduce capability to compete globally. Addressing this challenge is complex, although digital technologies and artificial intelligence (AI) models can improve resilience by assisting decision-making and mitigate risks, thus infusing greater predictability across the SC.

Supply chains are facing increasing disruptions and uncertainties owing to extreme weather events, the war in Ukraine, market volatility and the ongoing COVID-19 pandemic, among other factors. Manufacturing industries and their supply chains essentially create thousands of jobs that enable economic growth and sustain export capability. In addition, they need to maintain or increase both productivity and efficiency and recover quickly from unforeseen or unexpected challenges – that is they need to be resilient. Transformation initiatives, whether in production or supply chain management (SCM), are never easy. Process changes not supported by data or hurried human decisions can sometimes have unintended consequences, mainly adverse. However, in times of greater uncertainty (war and pandemic), setbacks can have greater consequences on the business. Manufacturers are already apprehensive and report slowing exports as recession concerns have caused consumers and businesses to pull back on spending. There is therefore a need to reduce uncertainty and augment resilience by unlocking and synthesising insights that emanate from the power of data analytics, AI and machine learning to improve the resilience efficiency balance.

This chapter will discuss the opportunities arising from the adoption and implementation of digital technologies and AI in SCM, leading to better value creation, less greenhouse gas emissions and resilience. The hurdles that enterprises are facing to integrate AI in their logistics and SCs will also be highlighted. This work comments on initiatives that uphold the objectives of SDG 8 – decent work and economic growth, SDG 9 – industry, innovation & infrastructure and SDG 13 – climate action.

The purpose of this study is to examine the relationships between market mavenism, tourists’ cocreation experience, loyalty and the mediating role of travel incentives in the post-COVID-19 tourism environment in the context of vaxication intentions in Turkey.

This study used covariance-based structural equation modeling to empirically test the proposed hypotheses. A total of 348 respondents participated in the survey.

The findings of this study support the assumption that market mavenism (MM) engage in cocreating and sharing travel experiences (CCTE). Furthermore, the study reveals that market mavens tend to demonstrate loyalty (LTY) toward service providers when engaging in cocreation with travel industry professionals. In addition, the study establishes the significant mediating effect of travel incentives (TI) between MM and vaxication intention (VI).

The study uses the theory of planned behavior to examine tourists’ intentions for vaxication and the psychological factors influencing their decisions, while also using the macro–micro theory to explore industry-level factors like market mavens and customer engagement, leading to a comprehensive understanding of COVID-19 vaccination and tourism behavior. Further research is needed to address limitations such as country diversity, multiple locations and service providers, online behavior analysis, authenticity perception and identification of market mavens’ personality traits and travel preferences.

This study contributes to the scholarly literature in several ways. First, it explores the influence of market mavens on tourism experience cocreation and customer loyalty during the postpandemic era. Second, it empirically examines the mediating role of travel incentives, adding to the understanding of market mavens and vaccination intentions. Lastly, the study addresses the implications during and after the COVID-19 for managers and service providers in the tourism industry.

This case study provides in-depth, practical knowledge to develop business strategies for the management program. After reading this case study, the students will be able to learn about the challenges and problems that service firms face during a crisis, the drastic changes in the market environment due to a crisis and the analysis tools that can be used when analyzing the shifted market environment. By analyzing this case study, students will be trained for the decision-making that arises in the process of crisis management in the hotel industry.

Nam Nghi Resort, situated on the picturesque Phu Quoc Island in Vietnam, experienced the tumultuous period of the COVID-19 pandemic. Before the pandemic, Nam Nghi was a thriving five-star resort, deeply rooted in Vietnamese culture and renowned for its luxurious amenities and breathtaking location. However, the onset of COVID-19 brought unprecedented challenges to the hospitality industry, leading to a sharp decline in tourism and revenue. Despite the adversity, Nam Nghi implemented risk management practices successfully and displayed resilience and adaptability. Through rigorous cost minimization, strategic facility upgrades and targeted marketing efforts, Nam Nghi managed to navigate the crisis and gradually rebuild its business as travel restrictions eased. As the industry began to show signs of recovery, the general manager faced new challenges in restoring the resort’s prepandemic vitality. The challenge remained of understanding changing consumer values and market dynamics.

This case study can be used as class material for Master of Business Administration (MBA) students. In particular, MBA students in the hospitality industry such as hotels, resorts, travel agencies and restaurants are the target audience.

Teaching notes are available for educators only.

CSS 12: Tourism and hospitality.