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Collaboration is an important emerging dimension of sustainable supply chain management. How to improve supply chain collaboration (SCC) by means of operational excellence approaches has become an important research topic. The Internet of things (IoT), an important means of operational excellence, has also received increased attention. For better collaboration by the IoT, this study proposes a novel methodology to evaluate the measures of IoT adoption in SCC.

Based on the six-domain model and the common classification of collaboration, the measures of the IoT and the criteria of SCC are developed, respectively. A hybrid multi-step methodology that combines neutrosophic set theory, analytic hierarchy process (AHP) and technology for order preference by similarity to an ideal solution (TOPSIS) is proposed to complete the evaluation.

The results show that improving information transparency, strengthening the integration of management information systems and improving large data processing abilities are the most important measures of the IoT in improving SCC. Measures such as introducing sensing technology and laser scanning technology rank at the bottom and are relatively unimportant.

The research results provide insights and references for firms to improve SCC by adopting appropriate IoT measures.

Most of existing studies indicate the significance of technology in SCC. But this study shows a different conclusion that technologies rank the bottom, while information transparency is more important. And a suitable explanation is given. It further enriches the theoretical studies in SCC field.

The purpose of this paper is to identify potential competitive relationships among brands by analyzing the dynamic clicking behavior of consumers.

Consumer sequential online click data, collected from JD.com, is used to analyze the dynamic competitive relationship between brands. It is found that the competition intensity across categories of products can differ considerably. Consumers exhibit big differences in purchasing time of durable-like goods, that is, the purchasing probability of such products changes considerably over time. The local polynomial regression model (LPRM) is used to analyze the relationship between brand competition of durable-like goods and the purchasing probability of a particular brand.

The statistical results of collective behaviors show that there is a 90/10 rule for the category durable-like goods, implying that ten percent of the brands account for 90 percent market share in terms of both clicking and purchasing behavior. The dynamic brand cognitive process of impulsive consumers displays an inverted V shape, while cautious consumers display a double V shaped cognitive process. The dynamic consumers’ cognition illustrates that when the brands capture a half of the click volume, the brands’ competitiveness reaches to its peak and makes no significant different from brands accounting for 100 percent of the click volume in terms of the purchasing probability.

There are some limitations to the research, including the limitations imposed by the data set. One of the most serious problems in the data set is that the collected click-stream is desensitized severely, restricting the richness of the conclusions of this study. Second, the data set consists of many other consumer behavioral data, but only the consumer’s clicking behavior is analyzed in this study. Therefore, in future research, the parameters brand browsing by consumers and the time of browsing in each brand should be added as indicators of brand competitive intensity.

The authors study brand competitiveness by analyzing the relationship between the click rate and the purchase likelihood of individual brands for durable-like products. When the brand competitiveness is less than 50 percent, consumers tend to seek a variety of new brands, and their purchase likelihood is positively correlated with the brand competitiveness. Once consumers learn about a particular brand excessively among all other brands at a period of time, the purchase likelihood of its products decreases due to the thinner consumer’s short-term loyalty the brand. Till the brand competitiveness runs up to 100 percent, consumers are most likely to purchase a brand and its product. That indicates brand competitiveness maintain 50 percent of the whole market is most efficient to be profitable, and the performance of costing more to improve the brand competitiveness might make no difference.

There are many studies on brand competition, but most of these research works analyze the brand’s marketing strategy from the perspective of the company. The limitation of this research is that the data are historical and failure to reflect time-variant competition. Some researchers have studied brand competition through consumer behavior, but the shortcoming of these studies is that it does not consider sequentiality of consumer behavior as this study does. Therefore, this study contributes to the literature by using consumers’ sequential clicking behavior and expands the perspective of brand competition research from the angle of consumers. Simultaneously, this paper uses the LPRM to analyze the relationship between consumer clicking behavior and brand competition for the first time, and expands the methodology accordingly.

The purpose of this paper is to prepare a spherical modifier-modified activated carbon fiber of high specific capacitance intended for electrode materials of supercapacitor.

In this study, phenolic-based microspheres are taken as modifiers to prepare PAN-based fiber composites by electrospinning, pre-oxidation and carbonization. Pearl-chain structures appear in RFC/ACF composites, and pure polyacrylonitrile fibers show a dense network. The shape and cross-linking degree are large. After the addition of the phenolic-based microspheres, the composite material exhibits a layered pearlite chain structure with a large porosity, and the RFC/ACF composite material is derived because of the existence of a large number of bead chain structures in the composite material. The density increases, the volume declines and the mass after being assembled into a supercapacitor as a positive electrode material decreases. The specific surface area of RFC/ACF composites is increased as compared to pure fibers. The increase in specific surface area could facilitate the diffusion of electrolyte ions in the material. Owing to the large number of bead chains, plenty of pore channels are provided for the diffusion of electrolyte ions, which is conducive to enhancing the electrochemical performance of the composite and improving the RFC/ACF composite and the specific capacitance of the material. The methods of electrochemical testing on symmetric supercapacitors (as positive electrodes) are three-electrode cyclic voltammetry, alternating current impedance and cycle stability.

The specific capacitance value of the composite material was found to be 389.2 F/g, and the specific capacitance of the electrode operating at a higher current density of 20 mA/cm2 was 11.87 F/g (the amount of the microsphere modifier added was 0.3 g). Using this material as a positive electrode to assemble into asymmetrical supercapacitor, after 2,000 cycles, the specific capacitance retention rate was 87.46 per cent, indicating excellent cycle stability performance. This result can be attributed to the fact that the modifier embedded in the fiber changes the porosity between the fibers, while improving the utilization of the carbon fibers and making it easier for electrolyte ions to enter the interior of the composites, thereby increasing the capacitance of the composites.

The modified PAN-based activated carbon fibers in the study had high specific surface area and significantly high specific capacitance, which makes it applicable as an efficient and environment-friendly absorbent, as well as an advanced electrode material for supercapacitor.