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Although brands have developed mobile applications (apps) to offer consumers new experiences, low app usage numbers indicate the need to develop a systematic, practical evaluation framework for branded app design that specifies concrete design features.

An expert review provides an overview of the design of current branded apps. On the basis of an extensive literature review, this article classifies state-of-the-art design features for branded apps according to a proposed evaluation framework that includes human–computer interaction (HCI)–related and marketing-related evaluation criteria. In an application of these evaluation criteria, the authors evaluate 73 branded apps issued by 11 top fast-moving consumer goods (FMCG) brands.

The expert review identifies strengths and weaknesses that are common to the design of current branded apps. These findings inform the set of design recommendations that this article offers, which includes 14 features common to all types of apps and 9 features specific to particular types of apps.

This research offers practical implications for app designers, who need to address design dimensions contained in the proposed framework including the HCI-related (mobile, social and user experience design features) and marketing-related (branding and customer relationship management design features) to create effective branded apps.

Design elements identified in prior literature remain abstract and do not prescribe a systematic or pragmatic approach to using them in practice. This study takes a multidisciplinary perspective (HCI, marketing and design science) to establish a practical evaluation framework for branded app designs.

Geographical conditions monitoring (GCM) has elicited significant concerns from the Chinese Government and is closely related to the “Digital China” program. This research aims to focus on object-based change detection (OBCD) methods integrating very-high-resolution (VHR) imagery and vector data for GCM.

The main content of this paper is as follows: a multi-resolution segmentation (MRS) algorithm is proposed for obtaining homogeneous and contiguous image objects in two phases; a post-classification comparison (PCC) method based on the nearest neighbor algorithm and an image-object analysis (IOA) technique based on a differential entropy algorithm are used to improve the accuracy of the change detection; and a vector object-based accuracy assessment method is proposed.

Results show that image objects obtained using the MRS algorithm attain the objectives of the “same spectrum within classes” and “different spectrum among classes”. Moreover, the two OBCD methods can detect over 85 per cent of the changed regions. The PCC strategy can obtain the categories of image objects with a high degree of precision. The IOA technique is easy to use and largely automated.

On the basis of the VHR satellite imagery and vector data, the above methods can effectively and accurately provide technical support for GCM implementation.

The purpose of this paper is to analyze the characteristics of spatio-temporal dynamics and the evolution of land use change is essential for understanding and assessing the status and transition of ecosystems. Such analysis, when applied to Horqin sandy land, can also provide basic information for appropriate decision-making.

By integrating long time series Landsat imageries and geographic information system (GIS) technology, this paper explored the spatio-temporal dynamics and evolution-induced land use change of the largest sandy land in China from 1983 to 2016. Accurate and consistent land use information and land use change information was first extracted by using the maximum likelihood classifier and the post-classification change detection method, respectively. The spatio-temporal dynamics and evolution were then analyzed using three kinds of index models: the dynamic degree model to analyze the change of regional land resources, the dynamic change transfer matrix and flow direction rate to analyze the change direction, and the barycenter transfer model to analyze the spatial pattern of land use change.

The results indicated that land use in Horqin sandy land during the study period changed dramatically. Vegetation and sandy land showed fluctuating changes, cropland and construction land steadily increased, water body decreased continuously, and the spatial distribution patterns of land use were generally unbalanced. Vegetation, sandy land and cropland were transferred frequently. The amount of vegetation loss was the largest. Water body loss was 473.6 km², which accounted for 41.7 per cent of the total water body. The loss amount of construction land was only 1.0 km². Considerable differences were noted in the rate of gravity center migration among the land use types in different periods, and the overall rate of construction land migration was the smallest. Moreover, the gravity center migration rates of the water body and sandy land were relatively high and were related to the fragile ecological environment of Horqin sandy land.

The results not only confirmed the applicability and effectiveness of the combined method of remote sensing and GIS technology but also revealed notable spatio-temporal dynamics and evolution-induced land use change throughout the different time periods (1983-1990, 1990-2000, 2000-2010, 2010-2014, 2014-2016 and 1983-2016).

This paper aims to propose an odor sensing system based on wide spectrum for e-nose, based on comprehensive analysis on the merits and drawbacks of current e-nose.

The wide spectral light is used as the sensing medium in the e-nose system based on continuous wide spectrum (CWS) odor sensing, and the sensing response of each sensing element is the change of light intensity distribution.

Experimental results not only verify the feasibility and effectiveness of the proposed system but also show the effectiveness of least square support vector machine (LSSVM) in eliminating system errors.

Theoretical model of the system was constructed, and experimental tests were carried out by using NO₂ and SO₂. System errors in the test data were eliminated using the LSSVM, and the preprocessed data were classified by euclidean distance to centroids (EDC), k-nearest neighbor (KNN), support vector machine (SVM), LSSVM, respectively.

The system not only has the advantages of current e-nose but also realizes expansion of sensing array by means of light source and the spectrometer with their wide spectrum, high resolution characteristics which improve the detection accuracy and realize real-time detection.

High-quality development of marine economy is a new concept put forward in response to the current national strategy in China. The purpose of this paper is to thoroughly understand the connotation and significance of high-quality development of marine economy through literature review, and further analyze the prospects for further research.

The authors first use the information visualization technology of CiteSpace to present a systematic review of the published literature from 2010 to 2019. Then, the authors analyze the researches on high-quality development of marine economy in terms of connotation, evaluation dimension, development path and guarantee mechanism.

Analysis results show that there is still insufficient understanding of the differences and links between the high-quality development of marine economy and the construction of marine power, intelligent ocean and transparent ocean.

Based on a thorough understanding of the subject, this paper puts forward the direction of further research on evaluation index system, path design scheme and policy system construction for high-quality development of marine economy.

Drawing upon the social identity theory, the authors argue that professionals' career identities have a positive indirect effect on identification with on-demand organizations through career networking behavior. In addition, the strength of these beneficial effects was also bound by extraversion and collectivism.

The hypothesized moderated mediation model was tested by multisource and time-lagged data about 242 Chinese accountants engaging in on-demand work.

The results demonstrated that professionals with a career identity tend to engage in career networking behaviors and identify themselves with a client company. In addition, extraverted professionals were more likely to engage in career networking behaviors, and collectivist professionals were more likely to identify with their on-demand organizations.

This research provides important guidelines on how managers in on-demand organizations leverage gig workers' career identities to establish deep relationships with them.

The authors expanded the traditional framework of identification in the setting of nontraditional work arrangements by establishing a link between career identity and organizational identification for on-demand professionals.

This paper assesses how discretionary accruals (DAs) affect corporate cash savings policies and the motivation behind this cash saving behavior and, also whether the linkage between DAs and cash saving affect the market-perceived cash value.

We construct the measure of DAs using the previous five-year average information to investigate the association of DAs with the change in cash. Moreover, the Faulkender and Wang (2006) methodology is utilized to examine the market-perceived cash value in DAs.

The key finding is that firms with high DAs save significantly more cash. A one standard deviation increase in DAs saves cash by 12.59%. Furthermore, the value of cash is low for these firms. The effect is stronger in firms with poor governance but not present in financially constrained firms.

The empirical evidence highlights DAs have negative effect on market-perceived cash value, which underscores the insight that managers manage earnings opportunistically using DAs.

Taken together, we provide more evidence on the literature of accruals in earnings manipulation.

Frontline employees’ proactive behaviors (i.e. job crafting) are critical to satisfying customers’ idiosyncratic needs. If the supervisors practice job crafting, their subordinates are more likely to mimic such behaviors. However, there has been limited research on how leaders’ job crafting can influence subordinates’ job crafting. This study aims to examine the cross-level mechanisms (i.e. trickle-down effects) of supervisors’ job crafting on the subordinates’ attitudes and performance. Specifically, such trickle-down effects can be explained via two cross-level mechanisms of the supervisors’ job crafting on the subordinates’ work engagement and performance: social learning mechanism and job demands-resources mechanism.

A three-wave cross-lagged study was conducted in two-week intervals. The valid responses from 67 supervisors and their 201 subordinates were collected. The data set was analyzed using multilevel Structural Equation Modeling.

The results demonstrated that the social learning and job demands-resources mechanisms are not independent. The supervisor’s job crafting improves employment relationships, subsequently encourages subordinates’ job crafting and ultimately enhances work engagement and work performance.

The findings suggested that hospitality organizations should encourage job crafting among supervisors and managers. A proactive hotel manager can establish strong employment relationships, motivate subordinates to work proactively and obtain positive work outcomes.

The findings enrich the knowledge about the trickle-down effects of supervisors on subordinates in terms of job-crafting behaviors. In particular, this study found a new theoretical perspective that the job demands-resources and social learning mechanisms may not be independent, and the subordinates’ perception of the employment relationship plays a critical role.

Since many global path planning algorithms cannot achieve the planned path with both safety and economy, this study aims to propose a path planning method for unmanned vehicles with a controllable distance from obstacles.

First, combining satellite image and the Voronoi field algorithm (VFA) generates rasterized environmental information and establishes navigation area boundary. Second, establishing a hazard function associated with navigation area boundary improves the evaluation function of the A^* algorithm and uses the improved A^* algorithm for global path planning. Finally, to reduce the number of redundant nodes in the planned path and smooth the path, node optimization and gradient descent method (GDM) are used. Then, a continuous smooth path that meets the actual navigation requirements of unmanned vehicle is obtained.

The simulation experiment proved that the proposed global path planning method can realize the control of the distance between the planned path and the obstacle by setting different navigation area boundaries. The node reduction rate is between 33.52% and 73.15%, and the smoothness meets the navigation requirements. This method is reasonable and effective in the global path planning process of unmanned vehicle and can provide reference to unmanned vehicles’ autonomous obstacle avoidance decision-making.

This study establishes navigation area boundary for the environment based on the VFA and uses the improved A* algorithm to generate a navigation path that takes into account both safety and economy. This study also proposes a method to solve the redundancy of grid environment path nodes and large-angle steering and to smooth the path to improve the applicability of the proposed global path planning method. The proposed global path planning method solves the requirements of path safety and smoothness.

Prefabricated components sustainable supplier (PCSS) selection is critical to the success of prefabricated projects. However, limited studies have addressed the uncertainty and complexities during the selection process, particularly in multi-criterion group decision-making (MCGDM) circumstances. Hence, the research aims to develop a group decision-making model using a modified fuzzy MCGDM approach for PCSS selection under uncertain situation.

The proposed study develops a framework for sorting decisions in PCSS selection by using the hesitant fuzzy technique for order preference by similarity to ideal solution (HF-TOPSIS) method. The maximum consistency (MC) model is used to calculate the weights of decision makers (DMs) based on the cardinality and sequence of decision data.

The proposed framework has been successfully applied and illustrated in the case example of CB01 contract section in Hong Kong-Zhuhai-Macao Bridge (HZMB) megaproject. The results show various complicated decision-making scenarios can be addressed through the proposed approach. The MC model is able to calculate the weights of DMs based on the cardinality and sequence of decision data.

The research contributes to improving accuracy and reliability decision-making processes for PCSS selection, especially under hesitant and fuzzy situations in prefabricated megaprojects.