The purpose of this paper is to investigate the adoption of an Activity-Based Costing (ABC) system to provide relevant cost information for enterprises in the business of building and selling Internet of Things (IoT) based products. The research is constructed over the relevant themes identified in previous research about ABC. An important issue that emerges from the analysis is that cost is a function of the volume of production and this notion of production does not represent the source of value generation discussed in this work. A functioning of a smart and connected product requires a cloud-based system for operating and monitoring it throughout its life. The implication of collecting and processing data is that costs essentially changes depending on the volume of data stored and the complexity of intended analytics that would require more qualified analysts. The estimation of costs related to data analytics and products’ monitoring serve as a reference to forecast future expending during the lifetime of products. This research is the first to provide a theoretical discussion on ABC assumptions in the context of IoT business models.

In this paper, an attempt has been made to develop a mathematical model in order to study the relationship between laser cutting parameters such as laser power, cutting speed, assist gas pressure and focus position, and kerf taper angle obtained in CO2 laser cutting of AISI 304 stainless steel. To this aim, a single hidden layer artificial neural network (ANN) trained with gradient descent with momentum algorithm was used. To obtain an experimental database for the ANN training, laser cutting experiment was planned as per Taguchi’s L27 orthogonal array with three levels for each of the cutting parameters. Statistically assessed as adequate, ANN model was then used to investigate the effect of the laser cutting parameters on the kerf taper angle by generating 2D and 3D plots. It was observed that the kerf taper angle was highly sensitive to the selected laser cutting parameters, as well as their interactions. In addition to modeling, by applying the Monte Carlo method on the developed kerf taper angle ANN model, the near optimal laser cutting parameter settings, which minimize kerf taper angle, were determined.

The purpose of this study is to analyze the effect of digital finance, digital marketing and digital payment variables on finance performance. This study uses quantitative methods and data analysis techniques is performed based on Structural Equation Modeling using SmartPLS 3.0 software. The method of selecting the sample using the snowball sampling methods. Online questionnaires were sent to 190 SMEs respondents in the province of Banten Indonesia and evaluated the returned questionnaires. The results of data analysis show that the digital finance had a positive and significant effect on the finance performance, the digital payment had a positive and significant effect on the finance performance and the digital marketing had a positive and significant effect on the finance performance. The findings of this research can provide benefits for MSME actors in developing their business to improve business performance, by paying attention to aspects of MSME digitization and financial literacy of MSME entrepreneurs. Keep in mind, the important role of information technology in business activities requires entrepreneurs to improve their digital literacy.

Maintenance Qualitn Function Deployment (MQFD) is a methodology for improving the quality and effectiveness of maintenance services in a manufacturing organization. One major part of it is House of Quality (HoQ). HoQ translates the experts’ voice into technical requirements for the improvement of maintenance quality. These data are generally vague in nature. Fuzzy numbers are generally used to represent vague data in HoQ. Since some parameters are predefined in fuzzy approach, the experts’ opinion may not be truly reflected in the HoQ analysis. In this work, a rough set - fuzzy approach, is proposed for MQFD to overcome this drawback.The objective of this model is to prioritize the technical requirements effectively with the proper reflection of customers/experts’ perceptions in the output. An illustrative example is presented to explain this approach.

This paper deals with the elastica and buckling loads of the nonlinear elastic tapered cantilever columns subjected to an axial load at the free end. The column cross section is rectangular, where the width and depth vary linearly with the column axis. The column material is nonlinear elastic, which obeys the Ludwick’s constitutive law. The ordinary differential equations governing the elastica of buckled column are derived and solved numerically for computing the elastica and buckling loads. Parametric studies for the annealed copper, N.P. 8 aluminum alloy and steel columns are conducted

Smart home services (SHSs) afford users an effective lifestyle management system, which provides human-oriented networking of smart devices and applications that enable users to control their homes from anywhere at any time. Despite the benefits of SHSs, however, their acceptance is very low. There remains a gap in the literature in terms of a comprehensive model that addresses users’ intention to use SHSs. To address this gap, the present study explored the factors that influence SHS acceptance among users based on well-established theoretical frameworks, such as the technology acceptance model, innovation diffusion theory, and the theory of planned behavior. To this end, the study integrated four additional factors, namely, perceived convenience, perceived connectedness, perceived cost, and perceived privacy risk, into the exploration and carried out structural equation modeling to quantitatively determine the effects of these factors. Questionnaires were administered to 750 users. The findings indicated that perceived compatibility, perceived convenience, perceived connectedness, perceived cost, perceived behavioral control with perceived usefulness, and perceived ease of use directly and indirectly exerted a significant influence on users’ intention to use SHSs.

The increasingly tight competition has caused problems for small and medium enterprises (SMEs) in increasing their marketing performance. During the last few years, the marketing performance of SMEs operating in the Project woodcraft industry sector in the Badung Bali has moved downwards. The goal of this research is to develop knowledge in the fields of Strategic Management, specifically regarding product innovation to achieve a competitive advantage in an attempt to improve internationalization and marketing performance. The population in this research is all of the SMEs operating in the woodcraft industry sector and is based in Badung Bali. The sample size in this research is determined based on Slovin's formula and the total includes 100 units of SME operating in the woodcraft industry. The method used is the quantitative approach, which examines the role of competitive advantage in mediating the influence of product innovation on internationalization and marketing performance. Based on the research results, product innovation has a positive and significant influence on both, competitive advantage and internationalization. Product innovation and competitive advantage have positive and significant influences on marketing performance. Competitive advantage has a positive and significant influence on internationalization. Meanwhile, it has been revealed that competitive advantage can mediate the influence of product innovation on marketing performance and competitive advantage can mediate the influence of product innovation on the internationalization of SME operating in the Project woodcraft industry sector in Badung Bali. Based on these findings, the project woodcraft industry SME in Badung Bali is advised to be more innovative in producing their products, so that there would be an increase in marketing performance in the international market. It is also recommended for subsequent researchers to add in other variables, such as product quality and market orientation, to enrich the information attained.

The social exchange perspective seeks to acknowledge, understand and predict the dynamics of social interactions. Empirical research involving social exchange constructs have grown to be highly technical including confirmatory factor analysis to assess construct distinctiveness and structural equation modeling to assess construct causality. Each study seemingly strives to assess how underlying social exchange theoretic constructs interrelate. Yet despite this methodological depth and resultant explanatory and predictive power, a significant number of studies report findings that, once synthesized, suggest an underlying persistent threat of conceptual or construct validity brought about by a search for epistemological parsimony. Further, it is argued that a methodological approach that embraces inherent complexity such as activity systems modeling facilitates the search for simplified models while not ignoring contextual factors.

This study is an inventory model with consideration of price, stock dependent demand, partially backlogged shortages, and two constant deterioration rates. In this model, demand function depends on price and stock while during the shortage time, demand depends only on price of the product. The deterioration is taken into account as a non-instantaneous, once the item is stocked in retailer’s house, any time deterioration can start with a constant rate for a certain period, then this deterioration rate increases. Shortages are allowed and it is partially backlogged. The corresponding inventory problem constitutes a non-linear constraint optimization problem. Here this problem has been solved using Lingo 15 software and also give 3D graph with the help of MATLAB2010a to show the convexity of the objective function. Finally, to illustrate and validate the inventory model, a numerical example is used considering fixed price. To study the effect of changes of different inventory parameters, a sensitivity analysis has been carried out changing one parameter at a time holding other parameters unchanged.

Multiple attribute decision making (MADM) methods are very useful in choosing the best alternative among the available finite but conflicting alternatives. TOPSIS is one of the MADM methods, which is simple in its methodology and logic. In TOPSIS, Euclidean distances of each alternative from the positive and negative ideal solutions are utilized to find the best alternative. In literature, apart from Euclidean distances, the city block distances have also been tried to find the separations measures. In general, the attribute data are distributed with unequal ranges and also possess moderate to high correlations. Hence, in the present paper, use of statistical distances is proposed in place of Euclidean distances. Procedures to find the best alternatives are developed using statistical and weighted statistical distances respectively. The proposed methods are illustrated with some industrial problems taken from literature. Results show that the proposed methods can be used as new alternatives in MADM for choosing the best solutions.