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Strategic alliances among organizations are some of the central drivers of innovation and economic growth. However, the discovery of alliances has relied on pure manual search and has limited scope. This paper proposes a text-mining framework, ACRank, that automatically extracts alliances from news articles. ACRank aims to provide human analysts with a higher coverage of strategic alliances compared to existing databases, yet maintain a reasonable extraction precision. It has the potential to discover alliances involving less well-known companies, a situation often neglected by commercial databases.

The proposed framework is a systematic process of alliance extraction and validation using natural language processing techniques and alliance domain knowledge. The process integrates news article search, entity extraction, and syntactic and semantic linguistic parsing techniques. In particular, Alliance Discovery Template (ADT) identifies a number of linguistic templates expanded from expert domain knowledge and extract potential alliances at sentence-level. Alliance Confidence Ranking (ACRank)further validates each unique alliance based on multiple features at document-level. The framework is designed to deal with extremely skewed, noisy data from news articles.

In evaluating the performance of ACRank on a gold standard data set of IBM alliances (2006–2008) showed that: Sentence-level ADT-based extraction achieved 78.1% recall and 44.7% precision and eliminated over 99% of the noise in news articles. ACRank further improved precision to 97% with the top20% of extracted alliance instances. Further comparison with Thomson Reuters SDC database showed that SDC covered less than 20% of total alliances, while ACRank covered 67%. When applying ACRank to Dow 30 company news articles, ACRank is estimated to achieve a recall between 0.48 and 0.95, and only 15% of the alliances appeared in SDC.

The research framework proposed in this paper indicates a promising direction of building a comprehensive alliance database using automatic approaches. It adds value to academic studies and business analyses that require in-depth knowledge of strategic alliances. It also encourages other innovative studies that use text mining and data analytics to study business relations.

This paper aims to consider the potential implications of the layering of regulation in relation to hydraulic fracturing (fracking) at the borders between the nations of the UK.

This paper uses a qualitative research method grounded in particular in legal geography to examine the existing approaches to regulating hydraulic fracturing and identify the places and their features that are constructed as a result of their intersection at the borders of the nations comprising the UK.

The current regulatory framework concerning hydraulic fracturing risks restricts the places in which the practice can occur in such a manner as to potentially cause greater environmental harm should the process be used. The regulations governing the process are not aligned in relation to the surface and subsurface aspects of the process to enable their management, once operational, as a singularly constructed place of extraction. Strong regulation at the surface can have the effect of influencing placement of the site only in relation to the place at which the resource sought reaches the surface, whilst having little to no impact on the environmental harms, which will result at the subsurface or relative to other potential surface site positions, and potentially even increasing them.

This paper is limited by uncertainty as to the future use of hydraulic fracturing to extract oil and gas within the UK. The issues raised within it would also be applicable to other extractive industries where a surface site might be placed within a radius of the subsurface point of extraction, rather than having to be located at a fixed point relative to that in the subsurface. This paper therefore raises concerns that might be explored more generally in relation to the regulation of the place of resource extraction, particularly at legal borders between jurisdictions, and the impact of regulation, which does not account for the misalignment of regulation of spaces above and below the surface that form a single place at which extraction occurs.

This paper considers the potential impacts of misaligned positions held by nations in the UK in relation to environmentally harmful practices undertaken by extractive industries, which are highlighted by an analysis of the extant regulatory framework for hydraulic fracturing.

Whilst the potential for cross internal border extraction of gas within the UK via hydraulic fracturing and the regulatory consequences of this has been highlighted in academic literature, this paper examines the implications of regulation for the least environmentally harmful placement of the process.

The motivation to participate in crowdsourcing (CS) platforms is an emerging challenge. Although researchers and practitioners have focused on crowd motivation in the past, the results obtained through such practices have not been satisfactory. Researchers have left unexplored research areas related to CS pillars, such as the evolution of the crowd’s primary motivations, seekers applying effective policies and incentives, platform design challenges and addressing task complexity using the synchronicity of the crowd. Researchers are now more inclined to address these issues by focusing on sustaining the crowd’s motivation; however, sustaining the crowd’s motivation has many challenges.

To fill this gap, this study conducted a systematic literature review (SLR) to investigate and map the challenges and factors affecting sustained motivation during CS with the overcoming implications. Studies that satisfied the inclusion criteria were published between 2010 and 2021.

Important sustainable factors are extracted using the grounded theory that has sustained participation and the factors' cohesion leads to the identification of challenges that the pillars of CS face. Crowds being the most vital part of CS contests face the challenge of engagement. The results reported the factors that affect the crowd’s primary and post-intentions, perceived value of incentives and social and communal interaction. Seekers face the challenge of knowledge and understanding; the results identify the reason behind the crowd’s demotivation and the impact of theories and factors on the crowd's psychological needs which helped in sustaining participation. Similarly, the platforms face the challenge of being successful and demanding, the results identify the latest technologies, designs and features that seekers proclaim and need the platforms designer's attention. The identified task challenges are completion and achievement; the authors have identified the impact of trait of task and solving mechanisms that have sustained participation.

The study identifies, explores and summarizes the challenges on CS pillars researchers are facing now to sustain contributions by keeping participants motivated during online campaigns. Similarly, the study highlights the implication to overcome the challenges by identifying and prioritizing the areas concerning sustainability through the adoption of innovative methods or policies that can guarantee sustained participation.

The purpose of this study is to use visual and inertial sensors to achieve real-time location. How to provide an accurate location has become a popular research topic in the field of indoor navigation. Although the complementarity of vision and inertia has been widely applied in indoor navigation, many problems remain, such as inertial sensor deviation calibration, unsynchronized visual and inertial data acquisition and large amount of stored data.

First, this study demonstrates that the vanishing point (VP) evaluation function improves the precision of extraction, and the nearest ground corner point (NGCP) of the adjacent frame is estimated by pre-integrating the inertial sensor. The Sequential Similarity Detection Algorithm (SSDA) and Random Sample Consensus (RANSAC) algorithms are adopted to accurately match the adjacent NGCP in the estimated region of interest. Second, the model of visual pose is established by using the parameters of the camera itself, VP and NGCP. The model of inertial pose is established by pre-integrating. Third, location is calculated by fusing the model of vision and inertia.

In this paper, a novel method is proposed to fuse visual and inertial sensor to locate indoor environment. The authors describe the building of an embedded hardware platform to the best of their knowledge and compare the result with a mature method and POSAV310.

This paper proposes a VP evaluation function that is used to extract the most advantages in the intersection of a plurality of parallel lines. To improve the extraction speed of adjacent frame, the authors first proposed fusing the NGCP of the current frame and the calibrated pre-integration to estimate the NGCP of the next frame. The visual pose model was established using extinction VP and NGCP, calibration of inertial sensor. This theory offers the linear processing equation of gyroscope and accelerometer by the model of visual and inertial pose.

Business process modeling can involve multiple stakeholders, so it is natural that problems may occur during the designing and understanding processes. One way to perceive these problems is to evaluate the comprehension of business process models through the collection of data related to the readers' eye movement via an eye-tracking device. The purpose of this paper is to provide a comprehensive overview of the use of eye-trackers in understanding process models and to offer a research roadmap to challenge the community to address the identified limitations and open issues that require further investigation.

To achieve this goal, Systematic Literature Review (SLR) was performed following good practices from the Evidence-Based Software Engineering's (EBSE) field.

This study resulted in 10 primary studies selected for analysis and data extraction, from the 1,482 initially retrieved. The major findings indicate that the business process community still benefits little from the use of eye-tracking, e.g. not offering sufficient support for inexperienced designers and not having an explicit standardization in its use. These and other findings are synthesized in a research roadmap which results would benefit researchers and practitioners.

In the studies found, the methods used to explore eyes' movement in process models' comprehension analysis were presented as an advantage of the current study. Additionally, another aspect presented in this SRL as an originality is presenting a set of open questions, suggesting valuable topics for future research through a research script (research roadmap).

The cycle of external indebtedness of dependent countries has become a huge constraint on any strategy for radical social change.

Argentina has recently entered a new process of debt overhang and renegotiation with the International Monetary Fund and private global creditors. The dominant debate around the country's foreign debt revolves around the conditions that can guarantee the sustainability of repayment. The underlying objective is to remain in the debt system that produces and reproduces dependency.

This chapter will seek to analyze the question of debt sustainability from another point of view: Is it possible to guarantee the (financial) sustainability of the debt at the same time as guaranteeing the sustainability of life? Our argument is that by remaining in the global debt system, Argentina creates conditions that violate the requirements for the sustainability of human and nonhuman life. Drawing on a discussion from Marxist dependency theory and the traditions of Marxist feminism and environmentalism, we will discuss how the debt sustainability argument presupposes the impossibility of reproducing life. In particular, we will show how the conditions required to guarantee debt sustainability in Argentina entail the deepening of the superexploitation of the “productive” and “reproductive” labor force, and the exacerbation of extractivism, putting social reproduction in crisis.

There is always a matching effect in advertising persuasion – the information that matches product characteristics or target consumer characteristics is considered to be relatively more persuasive. Based on the accessibility-diagnosability theory, this paper discusses the influence of the matching degree between the information presentation (vague description and precise description) and product attribute (vertical attribute and horizontal attribute) on people's attitudes toward advertising.

Study 1 aims to explore the impact of the matching effect of different information presentation methods (precise presentation vs vague presentation) and product attribute (horizontal attribute vs vertical attribute) on consumers' attitudes toward advertising; secondary data was used to support this research. Study 2 mainly used the situational simulated experiment to examine the results of study 1, and further explored the mediating mechanism of its matching effect.

The authors found that the matching degree between the information presentation method and product attribute will positively affect the fluency of advertising information processing, that is, the use of vague description of product vertical attribute can positively affect consumers' extraction fluency; while the use of precise description of product horizontal attribute can positively affect consumers' processing fluency, and both extraction fluency and processing fluency will positively affect consumers' attitude toward the advertisement.

An essential enlightenment of the research is that it sheds light on the interaction between product attribute (vertical attribute vs horizontal attribute) with the information presentation method (vague description vs precise description) from the perspective of accessibility-diagnosability theory, which explains consumers' information processing mechanisms in dealing with different advertising information.

The increasing importance and proliferation of text data provide a unique opportunity and novel lens to study human communication across a myriad of business and marketing applications. For example, consumers compare and review products online, individuals interact with their voice assistants to search, shop, and express their needs, investors seek to extract signals from firms' press releases to improve their investment decisions, and firms analyze sales call transcripts to increase customer satisfaction and conversions. However, extracting meaningful information from unstructured text data is a nontrivial task. In this chapter, we review established natural language processing (NLP) methods for traditional tasks (e.g., LDA for topic modeling and lexicons for sentiment analysis and writing style extraction) and provide an outlook into the future of NLP in marketing, covering recent embedding-based approaches, pretrained language models, and transfer learning for novel tasks such as automated text generation and multi-modal representation learning. These emerging approaches allow the field to improve its ability to perform certain tasks that we have been using for more than a decade (e.g., text classification). But more importantly, they unlock entirely new types of tasks that bring about novel research opportunities (e.g., text summarization, and generative question answering). We conclude with a roadmap and research agenda for promising NLP applications in marketing and provide supplementary code examples to help interested scholars to explore opportunities related to NLP in marketing.

This chapter relates Bunker's innovative view of nature, raw materials and political economy to the “global commodity chains” (GCCs) approach. The chapter contends that his view of the importance of primary material extraction, shipping, and energy used in various “transformations” of these crucial products can be fruitfully married to a GCCs perspective.

The purpose of this paper is to discuss the role of information and communication technology (ICT) for promoting environmental sustainability in a changing society. Isolated studies exist, but few take a holistic view. Derived from a Marxian tradition, the authors propose Ecological World Systems Theory (WST) as a holistic framework to assess the environmental impact of ICT. The theory is adapted responding to theoretical critiques of absence of change, namely state-centrism and structuralism.

Theoretical study. Empirical examples derived from already published literature.

Ecological WST focuses on the unequal distribution of environmental degradation, sees technological development as a zero-sum game rather than cornucopia and holds that technology is often seen as a fetish in today ' s society. The findings are that popular discourses on ICT and sustainability are since the 1990s becoming increasingly cornucopian, while conditions in the ICT value chain are less cornucopian.

Theoretical contributions to Marxian critiques of ICT, with more environmental focus than earlier Marxian critiques, for example Fuchs’ work. Develop a theoretical framework for ICT and sustainability which could be compared with works of e.g. Hilty, Patrignani and Whitehouse. The work is mostly based on existing empirical studies, which is a limitation.

This theoretical framework implies that unequal environmental degradation in different parts of the world should be taken into account when assessing environmental impact, for example by means of LCA.

The framework brings together questions of environmental effects of ICT and global justice.

The authors apply a rarely discussed theoretical framework to ICT and environmental sustainability. By doing this the authors suggest how the discourses and the value chain of ICT is intrinsically tied to the world system.