An Empirical Study of Factors Affecting e-Commerce Adoption among Small- and Medium-Sized Enterprises in a Developing Country: Evidence from Malaysia

The purpose of this paper is to empirically examine determinants of e-commerce adoption among Malaysian small- and medium-sized enterprises (SMEs). This study tested eight hypotheses on determinants affecting e-commerce adoption with empirical data from several survey instruments: an online questionnaire-based survey, mailed survey and questionnaire collected in-person from a sample of 307 SMEs in Malaysia. The findings show that e-commerce adoption within Malaysian SMEs is affected by perceived relative advantage, perceived compatibility, managers/owner's knowledge and expertise, management characteristics and external change agents. This study contributes to enhancing the understanding of the determinants of adopting e-commerce in SMEs and provides some interesting perspective from Malaysia. Those parties interested in promoting their business online may find these results helpful in guiding their efforts.     

Folksonomy link prediction based on a tripartite graph for tag recommendation

Nowadays social tagging has become a popular way to annotate, search, navigate and discover online resources, in turn leading to the sheer amount of user-generated metadata. This paper addresses the problem of recommending suitable tags during folksonomy development from a graph-based perspective. The proposed approach adapts the Katz measure, a path-ensemble based proximity measure, for the use in social tagging systems. We model a folksonomy as a weighted, undirected tripartite graph. We then apply the Katz measure to this graph, and exploit it to provide tag recommendations for individual users. We evaluate our method on two real-world folksonomies collected from CiteULike and Last.fm. The experimental results demonstrate that the proposed method improves the recommendation performance and is effective for both active taggers and cold-start taggers compared to existing algorithms.     

Silver (Ag) as a novel masking material in glass etching for microfluidics applications

In this paper, we report the use of a single masking film for deep glass etching in hydrofluoric acid (HF). Thin film silver (Ag) is the key masking material in this work enabling a simple and low cost fabrication of microfluidic structures. The Ag film was deposited by evaporation and etched in a diluted nitric acid and de-ionized water solution at a ratio of 1:3. Surface morphology for different thicknesses of Ag film and its correlation to the maximum achievable etch depth is analyzed. AFM results shows low roughness values (<5 nm), indicating the Ag films are of smooth surface. With a 100 nm Ag film, a 220 μm etch depth in borosilicate glass substrates were produced and by further thickening the Ag to 300 nm, etch depths exceeding 300 μm were successfully achieved. SEM images show that thinner Ag films are of finer grains, potentially a source for pinholes formation where rapid penetration of HF along the grain boundaries peels off the Ag film from the glass surface. However, the Ag film was found not to react with HF. The process was demonstrated in the fabrication of cavities for integration with other microfluidic devices.     

A flexible three-level logistic network design considering cost and time criteria with a multi-objective evolutionary algorithm

Nowadays, time and cost are familiar criteria for every logistic provider, and both have been long treated to be minimized simultaneously. However, the criteria are naturally conflicted even with flexibilities and/or constraints appeared in the logistic networks. This paper is concerned with three-level logistic networks with potential suppliers, distributed centers (DCs), and deterministic demands from available consumers. The networks also benefit from potential direct shipments from suppliers to consumers as long as suppliers and DCs facilities might face limited capacity in their own seasonal supplying and warehousing processes. The goal is (re)configure the networks in order to minimize response time to consumers, transportation cost and facility cost. Therefore, the networks are formulated as multiple criteria decision making problems, which have more than one configuration through the time and cost optimizing at the same time. Due to the flexibility and the constraints, the decision maker(s) needs a set of compromise solutions for the networks that represent optimal configurations based on the objectives without considering prior knowledge. To this end, the problems are formulated into four individual logistic network models varying with the flexibility option and/or the capacitated facilities. To find the compromise solutions, Pareto-based multi-objective evolutionary algorithm, NSGA-II is customized and then utilized to deal with an illustrative case study. The results are analyzed through the two performance measures, hypervolume and the number of optimal solutions obtained so far.     

Detection of stressed oil palms from an airborne sensor using optimized spectral indices

Existing vegetation indices and red-edge techniques have been widely used for the assessment of vegetation status and vegetation health from remote-sensing instruments. This study proposed and applied optimized Airborne Imaging Spectrometer for Applications (AISA) airborne hyperspectral indices in assessing and mapping stressed oil palm trees. Six vegetation indices, four red-edge techniques, a standard supervised classifier and three optimized AISA spectral indices were compared in mapping diseased oil palms using AISA airborne hyperspectral imagery. The optimized AISA spectral indices algorithms used newly defined reflectance values at wavelength locations of 734 nm (near-infrared (NIR)) and 616 nm (red). The selection of these two bands was based on laboratory statistical analysis using field spectroradiometer reflectance data. These two bands were then applied to the AISA airborne hyperspectral imagery using the three optimized algorithms for AISA data. The newly formulated AISA hyperspectral indices were D2 = R ₆₁₆/R ₇₃₄, normalized difference vegetation index a (NDVIa)?=?(R ₇₃₄ – R ₆₁₆)/(R ₇₃₄?+?R ₆₁₆) and transformed vegetation index a (TVIa)?=?((NDVIa?+?0.5)/(abs (NDVIa?+?0.5))?×?[abs (NDVIa?+?0.5)]^1/2. The classification results from the optimized AISA hyperspectral indices were compared with the other techniques and the optimized AISA spectral indices obtained the highest overall accuracy. D2 and NDVIa obtained 86% of overall accuracy followed by TVIa with 84% of overall accuracy.     

Investigation of chitosan‐g‐PEG grafted nanoparticles as a half‐life enhancer carrier for tissue plasminogen activator delivery

Tissue plasminogen activator (tPA) a thrombolytic agent is commonly used for digesting the blood clot. tPA half‐life is low (4–6 min) and its administration needs a prolonged continuous infusion. Improving tPA half‐life could reduce enzyme dosage and enhance patient compliance. Nano‐carries could be used as delivery systems for the protection of enzymes physically, enhancing half‐life and increasing the stability of them. In this study, chitosan (CS) and polyethylene glycol (PEG) were used for the preparation of CS‐g‐PEG/tPA nanoparticles (NPs) via the ion gelation method. Particles’ size and loading capacity were optimised by central composite design. Then, NPs cytotoxicity, release profile, enzyme activity and in vivo half‐life and coagulation time were investigated. The results showed that NPs does not have significant cytotoxicity. Release study revealed that a burst effect happened in the first 5 min and resulted in releasing 30% of tPA. Loading tPA in NPs could decrease 25% of its activity but the half‐life of it increases in comparison to free tPA in vivo. Also, blood coagulation time has significantly affected (p ‐value = 0.041) by encapsulated tPA in comparison to free tPA. So, CS‐g‐PEG/tPA could increase enzyme half‐life during the time and could be used as a non‐toxic candidate delivery system for tPA.Inspec keywords: drug delivery systems, nanofabrication, drugs, nanomedicine, coagulation, biomedical materials, cellular biophysics, enzymes, biochemistry, toxicology, molecular biophysics, biological tissues, blood, nanoparticles, polymersOther keywords: chitosan‐g‐PEG grafted nanoparticles, half‐life enhancer carrier, tissue plasminogen activator delivery, tPA half‐life, prolonged continuous infusion, enzyme dosage, polyethylene glycol, cytotoxicity, enzyme activity, encapsulated tPA, enzyme half‐life, blood coagulation, time 5.0 min     

Lipase‐catalyzed production of medium‐chain triacylglycerols from palm kernel oil distillate: Optimization using response surface methodology

Optimization of lipase‐catalyzed esterification for the production of medium‐chain triacylglycerols (MCT) from palm kernel oil distillate and glycerol was carried out in order to determine the factors that have significant effects on the reaction system and MCT yield. Novozyme 435 from Candida antarctica lipase was found to have the highest activity at 52.87 ± 0.03 U/g. This lipase also produced the highest MCT yield, which is 56.67%. The effect of different variables on MCT synthesis was studied with a two‐level five‐factor fractional factorial design. The various variables include (1) reaction temperature, (2) enzyme load, (3) molecular sieves concentration, (4) reaction time and (5) molar substrate ratio. Reaction temperature, reaction time and molar substrate ratio strongly affect MCT synthesis (p <0.05). However, enzyme load and molecular sieve concentration did not have a significant (p >0.05) influence on MCT yield. Therefore, the significant variables such as reaction temperature, reaction time and molar substrate ratio were further optimized through central composite rotatable design (CCRD). Comparisons between predicted and experimental values from the CCRD optimization procedures revealed good correlation, implying that the quadric response model satisfactorily expressed the percentage yield of MCT in the lipase‐catalyzed esterification. The optimum MCT yield is 73.3% by using 2 wt‐% enzyme dosage, a molecular sieves concentration of 1 wt‐%, a reaction temperature of 90 °C, a reaction time of 10 h and a molar substrate ratio of 4 : 1 (medium‐chain fatty acid/glycerol). Experiments to confirm the predicted results using the optimal parameters were conducted and an MCT yield of 70.21 ± 0.18% (n = 3) was obtained.