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This study aims to understand the relative intensity of the challenges and problems faced by small-scale entrepreneurs in Uttarakhand.

A survey methodology was used for this study. The judgement sampling method was used to select the sample for this study. The data were collected from 240 small-scale entrepreneurs using a self-structured questionnaire. Descriptive statistics, principal component analysis and confirmatory factor analysis were used to analyse the data.

The survey found that marketing, finance, taxation, human resource and government support–related problems are the major problems of small-scale entrepreneurs in the state.

This study was conducted in both rural and urban areas, but due to the unreachability of rural entrepreneurs, the representation of rural entrepreneurs is less, so the findings are more inclined towards urban entrepreneurs.

The research has highlighted the intensity of the major problems faced by small-scale entrepreneurs in Uttarakhand. Although many support schemes are operational in the state, small–scale entrepreneurs face many challenges, so this study provides solutions for those challenges.

This study is unique in that it measures the intensity of problems and challenges of small-scale entrepreneurs and provides insight into more serious issues prevalent in the state.

Coronavirus disease 2019 (COVID-19) outbreak has impacted catastrophically every sector of the economy throughout the world. And, the education sector is not leftover from the devastating effects of lockdown, especially in South Asia. It has led to the prolonged closure of schools/universities, subsequently, traditional teaching expeditiously transformed into online teaching. In the light of the events, this study is pertinent to examine teachers’ perceptions of online teaching and the obstacles they face in online teaching during this pandemic.

The research takes a quantitative and sample survey approach. A Google Form Questionnaire was used to obtain a sample of 200 Delhi school teachers in March and April 2021. Data were analyzed in SPSS by using Descriptive Statistics, Factor Analysis, Reliability and Chi-Square test, etc.

The result of the study indicates that on average, teachers have a positive perception about virtual teaching amid COVID-19 for reducing the learning gap and shaping pupils’ future during the crisis. Nevertheless, they encountered several obstacles in online teaching such as technical obstacles, difficulties in online exams and assessment, etc.

The findings of this study would persuade educational institutions and policymakers for enhancing the quality of online teaching by embracing the newest instructional strategies and providing continuous training to teachers.

Several studies described obstacles confronted by instructors in virtual teaching in higher education during the Coronavirus while disregarding the perception and challenges of school teachers toward e-learning in an ongoing outbreak. The present study replenishes this gap.

This study examines the causal relationship between intellectual capital and asset quality of banks in Ghana.

Using annual data extracted from audited financial statements of 24 banks from 2006 to 2015, a ratio of non-performing loans to gross loans and advances is employed to estimate asset quality growths while the value-added intellectual coefficient by Pulic (2008, 2004) measures intellectual capital. The panel-corrected standard errors estimation technique is used to estimate panel regressions with asset quality as the dependent variable.

Asset quality of banks in Ghana is generally not affected by intellectual capital. However, when intellectual capital is divided into its components, the study indicates that there are significant positive relationships between asset quality and two components of intellectual capital. Thus, structural capital and human capital efficiencies positively affect the asset quality of banks.

The findings of the study implore managements of banks to increase structural and human capital investments and efficiencies to improve asset quality. Furthermore, the results have direct implications on developments in financial markets in emerging economies.

The study analyses the link between typical intellectual capital and asset quality of banks which is yet to be empirically examined in an emerging banking market.

The purpose of this paper is to understand local perceptions on climate change and its impacts on biodiversity, rangeland, agriculture and human health.

A household survey with 300 interviewees and focus group discussions with key stakeholders were conducted and validated at two steps, using the climate data from the nearest weather stations and reviewing literatures, to correlate the local perceptions on climate change and its impacts.

Majority of the respondents reported an increase in temperature and change in the precipitation pattern with increased hazardous incidences such as floods, avalanches and landslides. Climate change directly impacted plant distribution, species composition, disease and pest infestation, forage availability, agricultural productivity and human health risks related to infectious vector-borne diseases.

Because of the remoteness and difficult terrain, there are insufficient local weather stations in the mountains providing inadequate scientific data, thus requiring extrapolation from nearest stations for long-term climate data monitoring.

The research findings recommend taking immediate actions to develop local climate change adaptation strategies through a participatory approach that would enable local communities to strengthen their adaptive capacity and resilience.

Local knowledge-based perceptions on climate change and its impacts on social, ecological and economic sectors could help scientists, practitioners and policymakers to understand the ground reality and respond accordingly through effective planning and implementing adaptive measures including policy formulation.

This research focuses on combining local knowledge-based perceptions and climate science to elaborate the impacts of climate change in a localised context in Rakaposhi Valley in Karakoram Mountains of Pakistan.

Blockchain technology is one of the emerging innovative technologies making waves globally, and it has been adjudged to have the capability to transform businesses. With the different capabilities of the technology, such as immutability of information and decentralisation of authority attributes, the built environment is slow in its adoption. This study aims to explore the barriers to the implementation of blockchain technology in the construction using a principal component analysis (PCA) approach.

This research took a post-positivist philosophical stance, which informed a quantitative research approach through a questionnaire survey. From the South African built environment and information technology sector, 79 respondents were drawn through a snowballing sampling technique. The built environment professionals include architect, construction project manager, construction manager, quantity surveyor and engineer. Retrieved data were screened and analysed by adopting the descriptive analysis and PCA while Cronbach alpha evaluated the reliability. Also, Kruskal–Wallis H non-parametric test was used to determine the differences in the opinion of the respondent groups.

The analysis revealed that all the identified barriers ranked above the average mean with lack of clarity, scalability risks and lack of skills or knowledge ranking top three. PCA clustered the identified barriers into three components: organisational barriers, social barriers and technological barriers.

This study was carried out in the Gauteng province of South Africa, leaving out other provinces due to accessibility, cost and time constraints.

Built environment organisations need to be kept abreast of the capabilities of blockchain technology as the major barrier observed was the lack of clarity of blockchain technology. Also, the technological barriers identified from this study need to be addressed by information technology experts to give consumers the desired value for money in implementing blockchain technology for the built environment.

The blockchain technology capabilities are incomparable to any other invention thus far. Therefore, it is very important that the numerous stakeholders in the built environment be made aware of the blockchain technology capabilities while formulating a solution to the identified barriers. This will aid its implementation in the built environment and help the industry measure up with its counterparts.

In the big data era, image compression is of significant importance in today’s world. Importantly, compression of large sized images is required for everyday tasks; including electronic data communications and internet transactions. However, two important measures should be considered for any compression algorithm: the compression factor and the quality of the decompressed image. In this paper, we use Frei-Chen bases technique and the Modified Run Length Encoding (RLE) to compress images. The Frei-Chen bases technique is applied at the first stage in which the average subspace is applied to each 3 × 3 block. Those blocks with the highest energy are replaced by a single value that represents the average value of the pixels in the corresponding block. Even though Frei-Chen bases technique provides lossy compression, it maintains the main characteristics of the image. Additionally, the Frei-Chen bases technique enhances the compression factor, making it advantageous to use. In the second stage, RLE is applied to further increase the compression factor. The goal of using RLE is to enhance the compression factor without adding any distortion to the resultant decompressed image. Integrating RLE with Frei-Chen bases technique, as described in the proposed algorithm, ensures high quality decompressed images and high compression rate. The results of the proposed algorithms are shown to be comparable in quality and performance with other existing methods.

Inter-organisational governance is an important enabler for information processing, particularly in relationships undergoing digital transformation (DT) where partners depend on each other for information in decision-making. Based on information processing theory (IPT), the authors theoretically and empirically investigate how governance mechanisms address information asymmetry (uncertainty and equivocality) arising in capturing, sharing and interpreting information generated by digital technologies.

IPT is applied to four cases of public–private relationships in the Dutch infrastructure sector that aim to enhance the quantity and quality of information-based decision-making by implementing digital technologies. The investigated relationships are characterised by differing degrees and types of information uncertainty and equivocality. The authors build on rich data sets including archival data, observations, contract documents and interviews.

Addressing information uncertainty requires invoking contractual control and coordination. Contract clauses should be precise and incentive schemes functional in terms of information requirements. Information equivocality is best addressed by using relational governance. Identifying information requirements and reducing information uncertainty are a prerequisite for the transformation activities that organisations perform to reduce information equivocality.

The study offers insights into the roles of both governance mechanisms in managing information asymmetry in public–private relationships. The study uncovers key activities for gathering, sharing and transforming information when using digital technologies.

This study draws on IPT to study public–private relationships undergoing DT. The study links contractual control and coordination as well as relational governance mechanisms to information-processing activities that organisations deploy to reduce information uncertainty and equivocality.

As focal firms in supply networks reflect on their experiences of the pandemic and begin to rethink their operations and supply chains, there is a significant opportunity to leverage digital technological advances to enhance socially responsible operations performance (SROP). This paper develops a novel framework for exploring the adoption of Industry 4.0 technologies for improving SROP. It highlights current best-practice examples and presents future research pathways.

This viewpoint paper argues how Industry 4.0 technology adoption can enable effective SROP in the post-COVID-19 era. Academic articles, relevant grey literature, and insights from industry experts are used to support the development of the framework.

Seven technologies are identified that bring transformational capabilities to SROP, i.e. big data analytics, digital twins, augmented reality, blockchain, 3D printing, artificial intelligence, and the Internet of Things. It is demonstrated how these technologies can help to improve three sub-themes of organisational social performance (employment practices, health and safety, and business practices) and three sub-themes of community social performance (quality of life and social welfare, social governance, and economic welfare and growth).

A research agenda is outlined at the intersection of Industry 4.0 and SROP through the six sub-themes of organisational and community social performance. Further, these are connected through three overarching research agendas: “Trust through Technology”, “Responsible Relationships” and “Freedom through Flexibility”.

Organisational agendas for Industry 4.0 and social responsibility can be complementary. The framework provides insights into how Industry 4.0 technologies can help firms achieve long-term post-COVID-19 recovery, with an emphasis on SROP. This can offer firms competitive advantage in the “new normal” by helping them build back better.

People and communities should be at the heart of decisions about rethinking operations and supply chains. This paper expresses a view on what it entails for organisations to be responsible for the supply chain-wide social wellbeing of employees and the wider community they operate in, and how they can use technology to embed social responsibility in their operations and supply chains.

Contributes to the limited understanding of how Industry 4.0 technologies can lead to socially responsible transformations. A novel framework integrating SROP and Industry 4.0 is presented.

Recently, disruptive technologies (DTs) have proposed several innovative applications in managing logistics and promise to transform the entire logistics sector drastically. Often, this transformation is not successful due to the existence of adoption barriers to DTs. This study aims to identify the significant barriers that impede the successful adoption of DTs in the logistics sector and examine the interrelationships amongst them.

Initially, 12 critical barriers were identified through an extensive literature review on disruptive logistics management, and the barriers were screened to ten relevant barriers with the help of Fuzzy Delphi Method (FDM). Further, an Interpretive Structural Modelling (ISM) approach was built with the inputs from logistics experts working in the various departments of warehouses, inventory control, transportation, freight management and customer service management. ISM approach was then used to generate and examine the interrelationships amongst the critical barriers. Matrics d’Impacts Croises-Multiplication Applique a Classement (MICMAC) analysed the barriers based on the barriers' driving and dependence power.

Results from the ISM-based technique reveal that the lack of top management support (B6) was a critical barrier that can influence the adoption of DTs. Other significant barriers, such as legal and regulatory frameworks (B1), infrastructure (B3) and resistance to change (B2), were identified as the driving barriers, and industries need to pay more attention to them for the successful adoption of DTs in logistics. The MICMAC analysis shows that the legal and regulatory framework and lack of top management support have the highest driving powers. In contrast, lack of trust, reliability and privacy/security emerge as barriers with high dependence powers.

The authors' study has several implications in the light of DT substitution. First, this study successfully analyses the seven DTs using Adner and Kapoor's framework (2016a, b) and the Theory of Disruptive Innovation (Christensen, 1997; Christensen et al., 2011) based on the two parameters as follows: emergence challenge of new technology and extension opportunity of old technology. Second, this study categorises these seven DTs into four quadrants from the framework. Third, this study proposes the recommended paths that DTs might want to follow to be adopted quickly.

The authors' study has several managerial implications in light of the adoption of DTs. First, the authors' study identified no autonomous barriers to adopting DTs. Second, other barriers belonging to any lower level of the ISM model can influence the dependent barriers. Third, the linkage barriers are unstable, and any preventive action involving linkage barriers would subsequently affect linkage barriers and other barriers. Fourth, the independent barriers have high influencing powers over other barriers.

The contributions of this study are four-fold. First, the study identifies the different DTs in the logistics sector. Second, the study applies the theory of disruptive innovations and the ecosystems framework to rationalise the choice of these seven DTs. Third, the study identifies and critically assesses the barriers to the successful adoption of these DTs through a strategic evaluation procedure with the help of a framework built with inputs from logistics experts. Fourth, the study recognises DTs adoption barriers in logistics management and provides a foundation for future research to eliminate those barriers.