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This study aims to synthesise and characterise new reactive dyes based on thiazole derivatives which act as chromophoric moieties. These dyes were applied to cotton fabric, resulting in the dyed fabrics exhibiting good colour strength, light fastness and other fastness properties. The antibacterial activity of the dyed cotton fabric was evaluated against gram-negative and gram-positive bacteria.

The dyes were synthesised in two steps. First, the coupling compound was formed by adding H-acid solution to cyanuric chloride in an ice bath at pH 5 then adding 4-aminobenzenesulphonic acid portion-wise at room temperature and at pH 6-7. Second, different diazonium salts 4-phenylthiazol-2-amine (2a) and 4-(4-methoxyphenyl) thiazol-2-amine (2b) were coupled with the coupling compound at pH 5. The resultant monochlorotriazine (MCT)-reactive dyes (6a, 6b) were formed. The synthesised dyes were applied onto cotton fabric under typical exhaust dyeing conditions and their dyeing properties were investigated.

High antimicrobial activity, dye exhaustion and fixation yield on cotton fabric were recorded for each dye. All dyes showed high stability against washing, rubbing, perspiration and light fastness.

Dyeing of cotton fabric with these dyes which have higher fastness, higher exhaustion and higher antibacterial activity is considered one of the most important reactive dyes species.

The preparation procedure showed the synthesis of the novel MCT-reactive dyes derived from thiazole derivatives followed by the application of these dyes on cotton fabrics.

Use of reactive dyes will bring a number of benefits to society including higher fastness and higher antibacterial activity so, and these dyes can be used for dyeing cotton.

In this work, the new reactive dyes derived from thiazole derivatives were synthesised and their structures were confirmed by the analytical and spectral data. Such compounds are considered to be excellent reactive dyes with different colour shades and higher antibacterial activity.

The purpose of this paper is to improve the socio-economic condition of low-income households in Malaysia, many products and services are available, including access to working capital and enterprise development training programs. This study examined the impact of access to working capital and micro-enterprise development training programs on household income and economic vulnerability among participants of development initiatives in the eKasih (national poverty data bank) in Peninsular Malaysia.

Adopting a cross-sectional design, the authors collected data randomly from the selected 300 micro-entrepreneurs from the list of development organizations available in the eKasih (national poverty data bank) located in four states of Peninsular Malaysia. Quantitative data were collected through structured interviews with the respondents from October to November 2017.

Both the length of participation and total amount of economic loan were found to increase the household income. However, there was no positive and significant impact of total number of training hours on household income. Interestingly, length of participation was found to reduce the level of economic vulnerability, except total amount of economic loan, and total number of training hours.

Despite the overwhelming empirical evidence, the findings indicated that the impact of enterprise development training programs was inconclusive. The effect of total amount of loan on economic vulnerability was also inconclusive. Hence, both policy makers and development organizations should understand how their programs benefit the poor households that can be improved through new implementation strategies.

Clean energy stocks are exhibiting signs of increasing volatility reflecting the varied and conflicting strategies employed by nations to pursue energy security objectives. In this regard, this paper aims to examine the response of NASDAQ clean energy stock returns volatility to the influences of external energy security elements including oil price, natural gas price, coal price, carbon price and green information technology stock price.

The paper uses symmetric and asymmetric generalised autoregressive conditional heteroskedasticity models (GARCH and TGARCH, respectively), which incorporate external energy security elements as exogenous variables, to estimate volatility models for clean energy stock returns.

Although, prices of oil, coal and natural gas are negatively associated with NASDAQ clean energy returns volatility, only the effect of natural gas price is significant. While carbon price affects NASDAQ clean energy returns volatility positively, green information technology price affects the volatility negatively. These results are robust to exponential GARCH and lead-and-lag robust ordinary least-squares as alternative estimation methods.

The study lumps the effects of all other external and internal factors, including internal energy security elements, in the autoregressive conditional heteroscedasticity (ARCH) term to predict NASDAQ clean energy returns conditional variance. GARCH method does not disentangle individual roles of the factors captured in the ARCH term in predicting volatility.

Results documented imply that natural gas appears a closer substitute for renewable energy sources than crude oil and coal, such that its price rise is perceived as good news in the NASDAQ clean energy financial market, while a fall is considered bad news. Furthermore, both an increase in carbon price and a decrease in green information technology stock performance are perceived as negative shocks.

In assessing risks associated with clean energy stocks, investors and fund managers should carefully consider the effects of external energy security elements.

To the best of the author’s knowledge, the paper is the first to identify external energy security elements and examine their effects on clean energy stock volatility.

Low-income households form a significant portion of the Malaysian population. To improve the socio-economic condition of low-income households, development organizations in Malaysia offer a wide range of development trainings, discussions and group or center meetings. This study aims to examine the impact of enterprise development training programs on entrepreneurial competencies among Peninsular Malaysia microentrepreneurs.

Adopting a cross-sectional design, the authors collected data from 300 randomly selected microentrepreneurs from the list of microentrepreneurs provided by eKasih (the National Poverty Data Bank), across four states of Peninsular Malaysia. Quantitative data were collected through structured interviews with the respondents from October to November 2017.

The findings revealed that enterprise development training programs significantly affected three of six entrepreneurial competencies (i.e. opportunity recognition competency, organizing competency and relationship competency). These findings highlight the importance of enterprise development training programs towards microentrepreneurs in increasing their competencies.

Through its insights, the study enriches the understanding of low-income communities in emerging economies, while offering significant practical implications. Based on findings, it is recommended that development organizations should therefore continue the current microenterprise development training programs. With improved entrepreneurial competencies, microentrepreneurs can thrive amidst competition yet sustaining business performance.

Service providers have a vested interest in enhancing adoption of technologies that improve the customer service experience. Buoyed by this idea, this paper aims to explore Latin American consumers’ mobile payment (MP) adoption, conceptualized as bank-sponsored mobile wallets that facilitate payment at the point-of-purchase. This paper applies a revised unified theory of acceptance and use of technology 2 (UTAUT2) model as theoretical framework for this exploration.

To test the conceptual model of MP adoption in Latin America put forward in this paper, the authors used Colombia as a sample site and conducted two studies among a sample of consumers in this country. Completed questionnaires from 186 participants (Study 1) and 398 participants (Study 2) were used in data analyses, which were conducted using Mplus 8.4 and PROCESS.

In Study 1, performance expectancy, social influence, bank trust, confidence in MP system and consumer innovativeness all impact consumers’ MP use intention; and use intention impacts MP behavior. In Study 2, involving a wider sample, performance expectancy, effort expectancy, facilitating conditions, perceived quality of the MP system, bank trust, consumer innovativeness, consumer optimism and consumer insecurity all affect MP use intention; and use intention significantly impacts MP behavior. Across both studies, follow-up analysis showed that effort expectancy influences performance expectancy for MP and indirectly influences MP use intention through its impact on performance expectancy. Bank trust also indirectly affects MP use intention through its effects on system confidence. In Study 2, age did not affect MP use intention or MP use; however, education affected MP use.

The theoretical underpinning for the conceptual model was the UTAUT2, and the results across the two studies support previous research in which this revised model has been useful in explaining technology adoption. Core elements of the UTAUT2 such as performance expectancy, effort expectancy, facilitating conditions and social influence had different impact on MP adoption in Latin America, depending on the sample. Technology readiness index motivators and inhibitors also aid understanding of MP adoption.

The research provides insights on the variables that members of the MP ecosystem in Latin America (e.g. banks and other service providers, card issuers) need to address in getting Latin American consumers to use MP.

This research extends the exploration of MP to a region of the world that has not been the focus of prior studies on the adoption of this technology and responds to calls by some researchers to increase research in this region. The conceptual models in the two studies also incorporate trust in the banks that are part of the MP ecosystem in Latin America and consumer overall confidence in this MP ecosystem. The results show that both these factors are influential in Latin American consumers’ adoption of MP. System confidence also mediates the relationship between bank trust and MP use intention.

The purpose of this research study is to extract and identify named entities from Hadith literature. Named entity recognition (NER) refers to the identification of the named entities in a computer readable text having an annotation of categorization tags for information extraction. NER is an active research area in information management and information retrieval systems. NER serves as a baseline for machines to understand the context of a given content and helps in knowledge extraction. Although NER is considered as a solved task in major languages such as English, in languages such as Urdu, NER is still a challenging task. Moreover, NER depends on the language and domain of study; thus, it is gaining the attention of researchers in different domains.

This paper proposes a knowledge extraction framework using finite-state transducers (FSTs) – KEFST – to extract the named entities. KEFST consists of five steps: content extraction, tokenization, part of speech tagging, multi-word detection and NER. An extensive empirical analysis using the data corpus of Urdu translation of Sahih Al-Bukhari, a widely known hadith book, reveals that the proposed method effectively recognizes the entities to obtain better results.

The significant performance in terms of f-measure, precision and recall validates that the proposed model outperforms the existing methods for NER in the relevant literature.

This research is novel in this regard that no previous work is proposed in the Urdu language to extract named entities using FSTs and no previous work is proposed for Urdu hadith data NER.

This paper reviews the academic contributions that have emerged to date on the broad definition of farm-level management information systems (MISs). The purpose is twofold: (1) to identify the theories used in the literature to study the adoption of digital technologies and (2) to identify the drivers of and barriers to the adoption of such technologies.

The literature review was based on a comprehensive review of contributions published in the 1998–2019 period. The search was both automated and manual, browsing through references of works previously found via high-quality digital libraries.

Diffusion of innovations (DOIs) is the most frequently used theoretical framework in the literature reviewed, though it is often combined with other innovation adoption theories. In addition, farms’ and farmers’ traits, together with technological features, play a key role in explaining the adoption of these technologies.

So far, research has positioned the determinants of digital technology adoption mainly within the boundaries of the farm.

On the practical level, the extensive determinants’ review has potential to serve the aim of policymakers and technology industries, to clearly and thoroughly understand adoption dynamics and elaborate specific strategies to deal with them.

This study’s contribution to the existing body of knowledge on the farm-level adoption of digital technologies is twofold: (1) it combines smart farming and existing technologies within the same category of farm-level MIS and (2) it extends the analysis to studies which not only focus directly on adoption but also on software architecture design and development.

For better mapping the path of intellectual capital (IC) research, the purpose of this paper is to selectively review empirical studies of IC published, and identify theories, components and three dimensions of analysis: national IC (NIC), regional IC (RIC) and organizational IC (OIC).

The systematic literature review (SLR) subject to analysis is based on empirical studies made between 1960 and 2016, and focuses on three dimensions of analysis: NIC, RIC and OIC. Four research questions were designed, using the following databases, namely, Web of Science, Scopus and Google Scholar, for data collection purposes.

The SLR unveils a multidimensional taxonomy for measuring and classifying the type of IC applicable to the different levels of analysis and provides some recommendations for future studies of NIC, RIC and OIC, by outlining the need for clear definitions of components and measures of IC and identifying strengths, limitations and future research avenues.

In order to fill the gap found in the literature and the non-existence of a study clarifying the multiple dimensions of analysis of IC, this SLR makes a twofold, original contribution to the literature on management: providing an SLR of the main empirical studies dealing with different units of analysis; and identifying a multidimensional taxonomy for measuring and classifying the type of IC applicable to the different levels of analysis.

This paper aims to study the effect of orange peel and moringa leaves extracts on microbiological safety, sensory quality, lipid oxidation and color properties of chicken sausages under frozen storage.

Chicken sausages were prepared by using orange peel, moringa leaves extracts and butylated hydroxytoluene (BHT). The sausages were stored in a freezer at −18°C. Samples were taken at a regular interval of 20 days from the day of production to spoilage of sausages and analyzed for microbiological safety, sensory quality, lipid oxidation and color properties.

In comparison to the control sausage, sausages having BHT, orange peel and moringa leaves extract had a significantly (p < 0.05) lower bacterial, yeast and mold count. All the sausages were microbiologically safe for consumption till the 100th day, and the results of the 120th day crossed the permissible limits. Sensory acceptability scores of sausages were good (>6) throughout the storage period. The color values of sausages were not affected by the addition of orange peel and moringa leaves extract. The extent of lipid oxidation increased during storage, and sausages with BHT, orange peel and moringa leaves extract had significantly (p < 0.05) lower values of thiobarbituric acid reactive substances and free fatty acids (FFAs) toward the end of the storage period.

The observations of this paper endorse the use of orange peel and moringa leaves extract in meat products formulation for acceptable storage stability under frozen conditions.