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In 2020, the logistics market in Malaysia was valued at USD 37.60 billion, and it is projected to grow to more than USD 55.0 billion by 2026 at a compound annual growth rate (CAGR) of more than 4%. However, more information is needed about the impact of green logistic practice determinants by the local SMEs on the market share. This study serves as a focal point by examining the factors involved by offering a conceptual framework of determinants and their potential outcomes. This study contributes by demonstrating a conceptual, theoretical framework derived from the synthesis of two theory such as the Resource-Based View theory and the Diffusion of Innovation Theory. At the same time, it offers a holistic approach with an in-depth understanding of the Technological and Organizational factors of SMEs. The relationship between the implementation of green practices and organizational performance is also explored.

This study examined the factors influencing willingness-to-repurchase for each class of airline service, and integrate the constructs of service quality, satisfaction and willingness-to-repurchase which were rooted on Engel-Kollat-Blackwell (EKB) model. The study focuses on the domestic and international arrival of passengers at Murtala Muhammed International Airport in Lagos and Nnamdi Azikwe International Airport in Abuja. Information was gathered from domestic and foreign passengers who had post-purchase experience and had used the airline's services more than once. The survey data were obtained concurrently from arrival passengers at two major international airports using an electronic questionnaire through random and purposive sampling techniques. The data was analysed using the ordinal logit model and structural equation model. From the 606 respondents, 524 responses were received but 489 responses were valid for data analysis and reporting and were obtained mostly from economy and business class passengers. The study found that the quality of seat pitch, allowance of 30 kg luggage permission, availability of online check-in 24 hours before the departing flight, quality of space for legroom between seats, and the quality of seats that can be converted into a fully flatbed are the major service factors influencing willingness-to-repurchase economy and business class tickets. Also, it was found that passengers' willingness to repurchase is influenced majorly by service quality, but not necessarily influenced by satisfaction. These results reflect the passengers' consciousness of COVID-19 because the study was conducted during the heat of COVID-19 pandemic. Recommendations were suggested for airline management based on each class.

This chapter seeks to quantify the effects of geographic access to community health centers on the likelihood of an individual having a regular source of health care.

Utilizing survey and center location data, the analysis employs bivariate cross-tabulation with chi-square and multinominal logistic regression to quantify the relationship between variables.

While individuals living in close spatial proximity to community health centers were more likely to identify a community health center as a regular source of care as compared with those without proximal access, the effect of community health center access on the identification of any source of regular health care was generally insignificant or negative, except for populations with a chronic medical condition.

While these findings support current literature suggesting that spatial proximity to care is insufficient to transform at-risk populations into regular primary care users, it is important to note that it is possible that individuals prefer to access primary care services outside of their immediate neighborhoods, potentially mediating the observed effect of proximity to care on the likelihood of having a regular source of care. Also, because this analysis is based on cross-sectional survey data, it is impossible to make a causal argument about the relationship between variables. Only the observed association can be asserted and used to inform future studies.

Existing research supports a positive association between community health center utilization and measures of health for social groups traditionally facing barriers to care, but few studies isolate the effect of center availability and health, particularly when considering those living in the catchment area but are not regular users. Due to the complexity and prevalence of barriers to health care for vulnerable and at-risk populations, these findings suggest that improving geographic access to primary health care does not guarantee positive outcomes for target groups. The magnitude of social disadvantage on vulnerable and at-risk populations can have a devastating effect on health care outcomes that is not easily overcome by social programs.

This chapter focuses on the heterogeneous pathways (including marital and cohabiting union and parenting histories) through which people navigate their family life courses from adolescence through mid-life, and their implications for union dissolution in middle and later life. The analyses draw on data (retrospective, cross-sectional) from the 2011 and 2017 Canadian General Social Surveys. The study sample includes individuals aged 50 and over (n = 14,547) who were in a union at age 50. Sequence analyses are used to identify the most common family life course trajectories among these individuals from adolescence through midlife (ages 15–50). Logistic regression analyses then address the implications of these trajectories for union dissolution in middle and later life (ages 50+). The results reveal four main family trajectories that characterize the earlier years of the adult life course: married with children, cohabiting with children, single or cohabiting without children, and married without children. These family trajectories, together with their level of complexity, play an important role in relation to both marital and cohabiting union dissolution outcomes in later life.

Purpose: The study aims to analyse and discuss the effect of COVID-19 on businesses. The chapter discusses the various machine learning (ML) tools and techniques, which can help in better decision making by businesses in the present world.

Need for the Study: COVID-19 has increased the role of VUCA elements in the business environment, and there is a need to address the challenges faced by businesses in such environment. ML and artificial learning can help businesses in facing such challenges.

Methodology: The focus and approach of the chapter are in the context of using artificial intelligence (AI) and ML techniques for decision making during the COVID-19 pandemic in a VUCA business environment.

Findings: The key findings and their implications emphasise the importance of understanding and implementing AI and ML techniques in business strategies during times of crisis.

Practical Implications: The chapter’s content is in the context of using AI and ML techniques during the COVID-19 pandemic and in a VUCA business environment.

High-quality nursing home (NH) care has long been a challenge within the United States. For decades, policymakers at the state and federal levels have adopted and implemented regulations to target critical components of NH care outcomes. Simultaneously, our delivery system continues to change the role of NHs in patient care. For example, more acute patients are cared for in NHs, and the Center for Medicare and Medicaid Services (CMS) has implemented value payment programs targeting NH settings. As a part of these growing pressures from the broader healthcare delivery system, the culture-change movement has emerged among NHs over the past two decades, prompting NHs to embody more person-centered care as well as promote settings which resemble someone's home, as opposed to institutionalized healthcare settings.

Researchers have linked culture change to high-quality outcomes and the ability to adapt and respond to the ever-changing pressures brought on by changes in our regulatory and delivery system. Making enduring culture change within organizations has long been a challenge and focus in NHs. Despite research suggesting that culture-change initiatives that promote greater resident-centered care are associated with several desirable patient outcomes, their adoption and implementation by NHs are resource intensive, and research has shown that NHs with high percentages of low-income residents are especially challenged to adopt these initiatives.

This chapter takes a novel approach to examine factors that impact the adoption of culture-change initiatives by assessing knowledge management and the role of knowledge management activities in promoting the adoption of innovative care delivery models among under-resourced NHs throughout the United States. Using primary data from a survey of NH administrators, we conducted logistic regression models to assess the relationship between knowledge management and the adoption of a culture-change initiative as well as whether these relationships were moderated by leadership and staffing stability. Our study found that NHs were more likely to adopt a culture-change initiative when they had more robust knowledge management activities. Moreover, knowledge management activities were particularly effective at promoting adoption in NHs that struggle with leadership and nursing staff instability. Our findings support the notion that knowledge management activities can help NHs acquire and mobilize informational resources to support the adoption of care delivery innovations, thus highlighting opportunities to more effectively target efforts to stimulate the adoption and spread of these initiatives.