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Information technology-enabled gig platforms connect freelancers with consumers to provide short-term services or asset sharing. The growth of gig economy, however, has been accompanied by controversy, and, recently, food delivery platforms have been criticized for using data-driven techniques to set strict delivery time limits, resulting in negative externality. This study aims to provide managerial implications on the decisions of delivery time and subsidy for food delivery platforms.

The authors develop an analytical framework to investigate the optimal delivery time and subsidy provided to delivery drivers to maximize the gig platform's profit and compare the results with those of a socially optimal outcome.

The study reveals that it is optimal for the platform to shorten the delivery time and raise the subsidy when the food price becomes higher; nevertheless, the platform should shorten the delivery time and lower the subsidy in response to a higher delivery fee. Increases in the food price or delivery fee have non-monotonic effects on the number of fulfilled orders and the platform's profit. In addition, the authors solve the socially optimal outcome and find that a socially optimal delivery time is longer than the platform's preferred length when the delivery fee is high and the negative externality is strong.

The food delivery platform's optimal decision on delivery time is derived after taking negative externality into account, which is rarely considered in the prior literature but is a practically important problem.

One of the major concerns of the constrained-surface stereolithography (SLA) process is that the built-up part may break because of the force resulting from the pulling-up process. This resultant force may become significant if the interface mechanism between the two contact surfaces (i.e. newly cured layer and the bottom of the resin vat) produces a strong bonding between them. The purpose of this paper is to characterize the separation process between the cured part and the resin vat by adopting an appropriate and simple mechanics-based model that can be used to probe the pulling-up process.

In this paper, the time-histories of the pulling-up forces are measured using FlexiForce® force sensors. The experimental data are analyzed and used to estimate the constitutive parameters of the separation mechanism. Here, the separation mechanism is modeled based on the concept of cohesive zone model (CZM) that is well-studied in the field of fracture mechanics. By using the experimentally measured pulling-up force, this paper proposes a very efficient inverse technique to estimate the constitutive parameters for the CZM. The constitutive laws for the CZM facilitate in relating the separation force at the interface between the cured part and the resin vat in terms of the pulling-up velocity. Unlike work proposed earlier, computationally expensive full-scale finite element runs are not essential in the current work while estimating the required parameters of the constitutive laws. Instead, mechanics-based computationally efficient surrogate model is proposed to readily estimate these constitutive parameters.

Two constitutive laws are compared on the basis of their predictions of the separation force profile. Excellent match is obtained between the measured and the predicted separation force profiles.

This paper selects a suitable mechanics-based model that can characterize the separation process and proposes a computationally efficient scheme to estimate the required constitutive parameters. The proposed scheme can be used to reliably predict the separation force for the constrained-surface SLA process, leading to improved productivity and reliability of the SLA processes in fabricating the built-up parts.

Advances in information technology now permit the recording of massive and diverse process data, thereby making data-driven evaluations possible. This study discusses whether teachers’ information literacy can be evaluated based on their online information behaviors on online learning and teaching platforms (OLTPs).

First, to evaluate teachers’ information literacy, the process data were combined from teachers on OLTP to describe nine third-level indicators from the richness, diversity, usefulness and timeliness analysis dimensions. Second, propensity score matching (PSM) and difference tests were used to analyze the differences between the performance groups with reduced selection bias. Third, to effectively predict the information literacy score of each teacher, four sets of input variables were used for prediction using supervised learning models.

The results show that the high-performance group performs better than the low-performance group in 6 indicators. In addition, information-based teaching and behavioral research data can best reflect the level of information literacy. In the future, greater in-depth explorations are needed with richer online information behavioral data and a more effective evaluation model to increase evaluation accuracy.

The evaluation based on online information behaviors has concrete application scenarios, positively correlated results and prediction interpretability. Therefore, information literacy evaluations based on behaviors have great potential and favorable prospects.

Internet referral services are a common form of online marketing operating activities. To incentivize infomediaries and improve referral performance, brand retailers typically apply the cost-per-click (CPC) or the cost-per-sale (CPS) payments. The purpose of this paper is to investigate the effect of referral services on the optimal contract with CPC or CPS payments.

This paper studies a mechanism design problem for internet referral services. To maximize the expected utility of the brand retailer, an uncertain contract model is established in which the brand retailer's assessment of the infomediary's referral service capability is characterized as an uncertain variable. Then equivalent models under CPC and CPS payments are presented to obtain the optimal solutions.

The results demonstrate that under CPC payments, as the referral service capability increases, the optimal sales volume is increasing, and the optimal transfer payment first shows a declining and then a rising trend. The brand retailer is less likely to raise the optimal transfer payment for the infomediary given a higher CPC revenue-sharing fee percentage, which is counterintuitive. Under CPS payments, the optimal sales volume and transfer payment are also increasing in the referral service capability. In addition, an increase in the click-through rate leads to the infomediary's incremental marginal utility.

The value of this research is its application of incentive contracts to the internet referral services considering CPC or CPS payments. The results of this research can serve as a guide for retailers and infomediaries in their decision-making around online retailing.

Polymer-particle composites, which have demonstrated wide applications ranging from energy harvesting and storage, biomedical applications, electronics and environmental sensing to aerospace applications, have been investigated for decades. However, fabricating polymer-particle composites with controlled distribution of particles in polymer continues to be a fundamental challenge. As to date, a few additive manufacturing (AM) technologies can fabricate composites, however, with a limited choice of materials or limited dispersion control. Against this background, this research investigated a hybrid polymer-particle composite manufacturing process, projection electro-stereolithography (PES) process, which integrates electrostatic deposition and projection based stereolithography (SL) technologies.

In PES process, a photoconductive film collects charged particles in the regions illuminated by light. Then, collected particles are transferred from the film to a polymer layer with defined patterns. Lastly, a digital mask is used to pattern the light irradiation of the digital micromirror device chip, selectively curing the photopolymer liquid resin and particles of that layer. By transferring particles from the photoconductive film to the photopolymer in a projection-based SL system, multi-material composites with locally controlled dispersions could be produced. A proof-of-concept PES testbed was developed. Various test cases have been performed to verify the feasibility and effectiveness of the developed approach.

Challenges in this novel AM process, including process design, particle patterning and transferring, are addressed in this paper. It is found that particles can be transferred to a layer of partially cured resin completely and accurately, by using the stamping approach. The transferring rate is related to stamping force and degree of conversion of the recipient layer. The developed hybrid process can fabricate polymer-particle composites with arbitrary dispersion pattern, unlimited printable height and complicated geometries.

Although an electrostatic deposition process has been investigated as a 3D printing technology for many years, it is the first attempt to integrate it with projection SL for fabricating multi-material polymer composite components. The novel hybrid process offers unique benefits including local dispersion control, arbitrary filling patterns, wide range of materials, unlimited printable height and arbitrary complicated geometries.

With the vigorous development of the e-commerce delivery service industry, delivery service has become an important factor for e-tailers to obtain the market competitive advantage. However, how to choose the best delivery service strategy is a difficult problem for e-tailers in practice. The purpose of this paper is to investigate the effect of delivery service on e-tailers and online platforms.

Based on the Stackelberg game, the research study establishes and solves three models, namely dual self-supporting delivery service model, dual third-party delivery service model and differential delivery service model.

The results show that when the self-supporting and third-party delivery cost coefficients are all small, no matter which delivery service providers the competitor selects, the e-tailer selects delivery with a lower service fee. When the self-supporting and third-party delivery service fee are all low, no matter which delivery service providers the competitor selects, the e-tailer selects delivery with a smaller service cost. Both service fee and service cost determine the choice of e-tailers' delivery strategy. When the commission rate is moderate, both e-tailers are willing to choose the self-supporting delivery strategy, but the platform only prefers to provide self-supporting delivery to them with a lower delivery service sensitivity coefficient.

This paper analyzes the optimal delivery service strategies for e-tailers to compete with competitors, and explores the impacts of parameters for e-tailers and online platforms in their decision-making. The findings provide valuable implications for relevant practices.

Based on the data from “Thousand village surveys” project of Shanghai University of Finance and Economics, we employ the ordered logistic method to do the empirical analysis on consumption, life and satisfaction (subjective well-being) of Chinese rural elderly. First, the result shows that the consumption (exclude medical expenses) has positive effect on the satisfaction of Chinese rural elderly, while the rural elderly are not preferred to compare with others. Good participation in social life and medical care condition could enhance the satisfaction of rural elderly. Second, the authors divided the sample into two groups as high-consumption group and low-consumption group. The result shows that the low-consumption group more tend to rely on their family members than high-consumption group. The authors suggest that in order to improve the rural elderly life satisfaction, the government needs to improve medical care system.

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly degrade the overall performance of engineering systems and change the feasibility of the obtained solutions. This paper aims to propose a multi-objective robust optimization approach based on Kriging metamodel (K-MORO) to obtain the robust Pareto set under the interval uncertainty.

In K-MORO, the nested optimization structure is reduced into a single loop optimization structure to ease the computational burden. Considering the interpolation uncertainty from the Kriging metamodel may affect the robustness of the Pareto optima, an objective switching and sequential updating strategy is introduced in K-MORO to determine (1) whether the robust analysis or the Kriging metamodel should be used to evaluate the robustness of design alternatives, and (2) which design alternatives are selected to improve the prediction accuracy of the Kriging metamodel during the robust optimization process.

Five numerical and engineering cases are used to demonstrate the applicability of the proposed approach. The results illustrate that K-MORO is able to obtain robust Pareto frontier, while significantly reducing computational cost.

The proposed approach exhibits great capability for practical engineering design optimization problems that are multi-objective and constrained and have uncertainties.

A K-MORO approach is proposed, which can obtain the robust Pareto set under the interval uncertainty and ease the computational burden of the robust optimization process.

Uncertainty is inevitable in real-world engineering optimization. With an outer-inner optimization structure, most previous robust optimization (RO) approaches under interval uncertainty can become computationally intractable because the inner level must perform robust evaluation for each design alternative delivered from the outer level. This paper aims to propose an on-line Kriging metamodel-assisted variable adjustment robust optimization (OLK-VARO) to ease the computational burden of previous VARO approach.

In OLK-VARO, Kriging metamodels are constructed for replacing robust evaluations of the design alternative delivered from the outer level, reducing the nested optimization structure of previous VARO approach into a single loop optimization structure. An on-line updating mechanism is introduced in OLK-VARO to exploit the obtained data from previous iterations.

One nonlinear numerical example and two engineering cases have been used to demonstrate the applicability and efficiency of the proposed OLK-VARO approach. Results illustrate that OLK-VARO is able to obtain comparable robust optimums as to that obtained by previous VARO, while at the same time significantly reducing computational cost.

The proposed approach exhibits great capability for practical engineering design optimization problems under interval uncertainty.

The main contribution of this paper lies in the following: an OLK-VARO approach under interval uncertainty is proposed, which can significantly ease the computational burden of previous VARO approach.

The study here responds to the view that the crucial problem in strategic management (research) is firm heterogeneity – why firms adopt different strategies and structures, why heterogeneity persists, and why competitors perform differently. The present study applies complexity theory tenets and a “neo-configurational perspective” of Misangyi et al. (2016) in proposing complex antecedent conditions affecting complex outcome conditions. Rather than examining variable directional relationships using null hypotheses statistical tests, the study examines case-based conditions using somewhat precise outcome tests (SPOT). The complex outcome conditions include firms with high financial performances in declining markets and firms with low financial performances in growing markets – the study focuses on seemingly paradoxical outcomes. The study here examines firm strategies and outcomes for separate samples of cross-sectional data of manufacturing firms with headquarters in one of two nations: Finland (n = 820) and Hungary (n = 300). The study includes examining the predictive validities of the models. The study contributes conceptual advances of complex firm orientation configurations and complex firm performance capabilities configurations as mediating conditions between firmographics, firm resources, and the two final complex outcome conditions (high performance in declining markets and low performance in growing markets). The study contributes by showing how fuzzy-logic computing with words (Zadeh, 1966) advances strategic management research toward achieving requisite variety to overcome the theory-analytic mismatch pervasive currently in the discipline (Fiss, 2007, 2011) – thus, this study is a useful step toward solving the crucial problem of how to explain firm heterogeneity.