AN ANALYSIS OF PERSONAL INFORMATION MANAGEMENT – A STUDY OF E-MAIL USAGE BY THE STUDENTS OF THE UNIVERSITY OF SHEFFIELD
Abstract:
AN ANALYSIS OF PERSONAL INFORMATION MANAGEMENT – A STUDY OF E-MAIL USAGE BY THE STUDENTS OF THE UNIVERSITY OF SHEFFIELD
This study examined the students of the University of Sheffield as the research respondents to analyze whether there exists E-mail overload or not with all the advanced features provided by E-mail services today to avoid E-mail overload.
Initially when E-mail services were introduced, it was very helpful for people to communicate with the world within seconds, which broke the communication gaps, gradually, the E-mail services evolved where in it can be used for various number of tasks which makes life easier. Gradually with the development of E-mail services the inboxes started to grow slowly leading to large inboxes filled with few unwanted E-mails, this has led to losing a few important E-mails, which are lost in the large inboxes and retrieving them were difficult for few (Studies by Various Authors).
This study looks at the University students to analyze whether they are facing E-mail overload issues. In case they are facing overload issues, an effort has been made to understand how they are managing their E-mails. In this direction, the researcher has collected information from the various categories of students pursuing various levels of education. These students are basically divided into three categories (UG, PG, & Ph.D. students) to study whether there is any difference among the categories in rationalizing their inboxes.
The study tried to analyze various research variables to understand the techniques used by various students to avoid E-mail overload by which they are successful in it. Along with such techniques few additional recommendations are given to overcome the issue of overload and have to clean the inboxes.
Table of Contents
CHAPTER 1: INTRODUCTION
CHAPTER-2: LITERATURE REVIEW AND IDENTIFICATION OF THE RESEARCH PROBLEM
2.0 Personal Information Management
2.1 E-mail Background
2.2 Information Over-Load
2.3 E-mail Over-Load
2.4 Information Obesity
2.5 Digital Literacy
2.6 Digital Natives and Immigrants
2.7 Information Retrieval
CHAPTER-3: RESEARCH METHODOLOGY
3.1 Introduction
3.2 Research Design
3.3 Research Model
3.4 Data Collection Methods
3.5 Interview Technique
3.6 Data Coding
3.7 Data Cleaning
3.8 Tools for the Data Analysis
CHAPTER-4: RESULTS and DISCUSSION
CHAPTER-5: RECOMMENDATIONS
CHAPTER-6: CONCLUSIONS
References
Appendix
CHAPTER 1: INTRODUCTION
Information overload/over-burden has been an obviously recognized problem since the early 1970s, when Herbert Simon (1971) expressed “a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it” (p.40). However, the issue has been studied in the field of Information/Data Science, the examination has not been generally recognized by professionals in different fields who may be affected by a portion of its rising discoveries. In today’s online education, information overload has been assumed to be a significant factor as most of the conversation between the university staff and the students are through E-mails.
Personal Information Management (PIM) is frequently a burden for most of the people, and therefore much of an effort has been put in to improve PIM interfaces (Jones and Teevan, 2007). However, there is lack of empirical research on these PIM services which are widely used by “millions of users, multiple times a day” (Beyth & Nachmias, 2003).
About 97 Billion messages were sent and received through E-mails in the year 2007 (IDC 2007). Now in the digital era the number of E-mails sent per day has increased to 269 billion in 2017 (Tschabitscher, 2018). This means that the data is constantly generated in huge amounts, which may lead to information overload and may become hard for individuals to organize and retrieve their personal data. Therefore, this research focuses on E-mail overload and E-mail management by the students of the University of Sheffield to study the various techniques adopted by the students to overcome E-mail overload and also to look at whether they are successful in it or not. To answer this question six research questions were formulated which are presented as follows;
RQ-1: Whether E-mail overload exists with the students of the University of Sheffield in the present juncture?
RQ-2: If it exits is there any difference between various categories of students (UG, PG and Ph.D.) in organizing E-mails to avoid overload.
RQ-3: Whether the students of the University of Sheffield are successful in rationalising their inboxes?
RQ-4: Whether the E-mails from the university are causing information obesity to students?
RQ-5: Are the students facing E-mail stress?
RQ-6: What are the differences between E-mail management in the present and in the past?
CHAPTER-2: LITERATURE REVIEW AND IDENTIFICATION OF THE RESEARCH PROBLEM
2.0 Personal Information Management: Personal Information Management plays an important role in collection, storage, organizing and retrieval of digital objects (e.g. files, addresses and bookmarks) in every individual personal computing environment (Boardman and Sasse, 2004). Although there are many definitions of PIM, the following definition given by Jones and Teevan (2007) is widely cited: “Personal Information Management or PIM is both the practice and the study of the activities people perform to acquire, organize, maintain, retrieve, use and control the distribution of information items such as documents (paper‐based and digital), Web pages, and e‐mail messages for everyday use to complete tasks (work‐related and not) and to fulfill a person's various roles (as parent, employee, friend, member of community, etc.)”. There is a difference between PIM and “General Information Management (GIM)” according to Bergman, Beyth, & Nachmias (2003). GIM refers to someone manages information for a range of other people, whereas PIM refers to individuals managing his/her own information.
Of these PIM services, E-mail is one of the earliest and best computer applications, which is in practice from the last about 50 years. E-mails are widely used every day to communicate with friends and family (Grevet et.al, 2014). E-mail usage at work is the most efficient way to communicate with the co-workers. It is clearly evident that electronic mail has become the most predominant forms of communication, however E-mail is not only used to communicate in the form of letters, it has also replaced telephone services in many professional environments (Dabbish, & Kraut, 2006). Tschabitscher (2018) in his work he has given various advantages of E-mails, which talks about speed, convenience where lengthy conversation which might take more time on phone calls. Files and images can be easily attached in an E-mail, E-mail records very conversation with time and data, E-mails have a capacity of unlimited space and also have no restrictions, and free communication unlike other communicative services which are quite expensive and does not store any information unlike the E-mails.
Goldberg (2007) in his work he has mentioned that in 2006 itself about 84 billion messages were sent daily through E-mail. E-mail messages likewise now incorporate more types of data, which includes -message exchange undertakings, critical individual and hierarchical declarations, meeting demands, shared archives and different sorts of such data. E-mails are cost effective and reach the destination without much time.
Whittaker and Sidner (1996) in their work they have said that E-mails have both positive and negative aspects. Though this is an old work, this work was taken into consideration as the start of this research from them. However, the empirical information demonstrates that E-mail was initially outlined as communication application; now it is being utilized for different purposes, which are discussed above leading to over-burden or also called as Information overload (Whittaker and Sidner, 1996). Information Over burden/overload is a situation where large information stacks and accessing them becomes difficult over a period of time. However, mass production has made easy to access this large information and there is no problem in finding the Information needed, but the problem is managing, filtering and arranging them in order has become very difficult. Quality drops when quantity rises, and it creates problems to users in managing their personal information. Users frequently have large in-boxes containing many messages, including outstanding tasks, incomplete read reports and conversational strings. Users attempt to manage their inboxes with various techniques, but are often unsuccessful with overlooking the important messages, which might be lost in the archives.
The present research explains how the students of the University of Sheffield face overburden/overload issues and tried to find out whether E-mail overload still exists in the email accounts of the students and the strategies, which most of the students adopted to minimize them. To study these issues, the following aims and objectives are formulated. Anyway, before formulating the aims and objectives an effort has been made to review the existing literature to understand the issues clearly and make an effort to identify the research gaps.
After going through the vast literature, an effort has been made to classify the review into various categories, which are presented below;
2.1 E-mail Background: E-mail has been the focus of research in the field of communication and technologies and PIM. To understand the issues clearly an effort is made to review the existing literature relating to the PIM and the Use of E-mail services. A summary of related work in the area of E-mails has been discussed, however the past work is mainly carried out in the environment or professional Email accounts. In this research we turn it to the strategies adopted by the student of the university of Sheffield in organizing their inboxes.
Whittaker and Sidner (1996) in their work they have said that there are a huge number of E-mail clients, who frequently spend huge amount of their time utilizing E-mail, inquire about recommends that E-mail has added to the development of distributed organizations, enabling individuals in various geographical territories to communicate across time and space. It has opened opportunities to the rise of online groups by supporting asynchronous communication. Email has been subject of numerous examinations, including pioneering early work that concentrated on the social and communicative aspects of E-mail, contrasting its use with face-toface communication. E-mails were initially intended for non-concurrent communication, however, as our investigation appears; E-mail has developed to a point where it is presently used for multiple purposes. Singh’s (2018) work reveals that the E-mail is being used for document delivery and archiving, work task delegation, task tracking and cloud storage. Their investigation further revealed that the members were highly positive about E-mail as a specialized communication tool. They focused on how E-mail empowered them to team up with other people crosswise, over time and separation, members additionally called attention to its favorable circumstances over different advancements, for example, phone and even face-to-face interactions.
Certain people experienced significant issues in perusing and answering E-mail in an auspicious way, with accumulations of unanswered E-mail and in discovering data in E-mail frame works. The powerlessness to effectively manage interactions means reduced responsiveness and loss of information which leads to E-mail overload. The same study identified that the E-mail inboxes were filled with read as well as unread messages. Originally E-mail support was designed for a synchronous communication. Clients could visit their inbox, read and respond to a message and erase or record that message. As indicated by this "one-touch demonstrate, messages are either new or documented". The inbox thus would be relied upon to contain just a predetermined number of new messages. Whatever it may be, Whittaker and Sidner’s discoveries did not bolster the onetouch PREVIEW 13 show. The one-touch demonstration neglected to precisely speak to - how most people utilized and dealt with their inboxes.
2.2 Information Over-Load:
Bertram Gross coined the term “information overload” in his 1964 work, and Gross defined information overload as “Information overload occurs when the amount of input to a system exceeds its processing capacity. Decision makers have fairly limited cognitive processing capacity. Consequently, when information overload occurs, it is likely that a reduction in decision quality will occur.”
Managing the incoming data from social media, e-mails, web-pages, mobile apps, etc. has become a problem to almost everyone in their daily lives. According to Zanarini (2018) the main causes of information overload are as follows:
• New information is being generated constantly in huge volumes.
• The simplicity of creating and sharing the information online.
• Easy to expand storage in computers and E-mails.
• No basic techniques for rapidly handling, contrasting and assessing data sources.
2.3 E-mail Over-Load: E-mail overload is a reality today, it is evident that more E-mails are received than needed today, more time and energy is consumed everyday dealing with messages, one statistic from two years back reports that normal office worker spends little more than four hours daily on E-mails (Jones, 2018). However, there are many definitions of E-mail overload Dabbish and Kraut (2006) suggests that E-mail overload occurs when an individual receives more E-mails than the individual can handle which strongly suggests that user plays an important role for explaining E-mail overload issue. According to Grevet et al. (2014) E-mail overload can occur in two ways, “receiving a large volume of incoming E-mails” and “having E-mails of different status types (to do, to read, etc.). Radicati Group (2017) and Roy (2017) have estimated that the number of Email users worldwide will grow to 2.9 bn. by 2019 and the number of E-mails sent out per day is estimated around 246 bn in 2019. 2.2 Information Over-Load: Bertram Gross coined the term “information overload” in his 1964 work, and Gross defined information overload as “Information overload occurs when the amount of input to a system exceeds its processing capacity. Decision makers have fairly limited cognitive processing capacity. Consequently, when information overload occurs, it is likely that a reduction in decision quality will occur.”
Managing the incoming data from social media, e-mails, web-pages, mobile apps, etc. has become a problem to almost everyone in their daily lives. According to Zanarini (2018) the main causes of information overload are as follows:
• New information is being generated constantly in huge volumes.
• The simplicity of creating and sharing the information online.
• Easy to expand storage in computers and E-mails.
• No basic techniques for rapidly handling, contrasting and assessing data sources.
2.3 E-mail Over-Load: E-mail overload is a reality today, it is evident that more E-mails are received than needed today, more time and energy is consumed everyday dealing with messages, one statistic from two years back reports that normal office worker spends little more than four hours daily on E-mails (Jones, 2018). However, there are many definitions of E-mail overload Dabbish and Kraut (2006) suggests that E-mail overload occurs when an individual receives more E-mails than the individual can handle which strongly suggests that user plays an important role for explaining E-mail overload issue. According to Grevet et al. (2014) E-mail overload can occur in two ways, “receiving a large volume of incoming E-mails” and “having E-mails of different status types (to do, to read, etc.). Radicati Group (2017) and Roy (2017) have estimated that the number of Email users worldwide will grow to 2.9 bn. by 2019 and the number of E-mails sent out per day is estimated around 246 bn in 2019. Whittaker and Sidner (1996) studied the behaviour of E-mail users, they have got E-mail information from twenty representatives working in the product business. Their outcomes drove them to coin the term E-mail overload as the utilization of E-mail for volumes that it was not intended for. The study examined 20 participants representing four major job types 1. Four high level managers, 2. Five first level managers, 3. Nine professional workers with no management responsibility, and 4. Two administrative assistants. They collected quantitative data from the participants which included (a) total number, age, and size of messages in their mailbox; (b) number of messages in each archival folder, (c) conversational threads, they couldn’t collect data from all 20 participants due to technical difficulties, only 18 user’s data were collected. They also interviewed all the 20 participants for 1-2 hours using semi-structured questions which are: (a) the volume of the E-mail they sent and received, (b) prioritization while reading and replying, (c) correspondence management, (d) filing behaviour (e) problems with E-mails, (f) reactions to certain technical solutions.
With the analysis of the data the authors discovered that participants were highly positive about the E-mail services as the best communication tool and also, they expressed how easy it was to communicate with people across the globe with less time and also quoted some advantages over other communication tool like telephone and postal services. However, some participants had problems in reading and replying to E-mail messages, felt difficulties in finding the information they need in the E-mail system. They also discovered clients appropriating the E-mail customers to perform, undertaking administration and individual filing or data administration.
According to the same authors the meaning of E-mail `over-load’ would fill in as the reason for a great part of the subsequent exploration on the utilization of E-mail customers for numerous capacities. Different scientists have noticed that after a long time since Whittaker and Sidner's work, the E-mail customer PREVIEW 12 had turned into a living space for the numerous E-mail clients (Ducheneaut and Bellotti, 2001). The authors revealed that to set the examples they had conducted investigation, which includes twenty-eight experts from three innovative firms. The examination demonstrated that these experts were basically living in their E-mail customers. They led a large portion of their work from their E-mail customers and utilized the customers for their personal task.
After ten years of Whittaker and Sidner’s (1996) study Further, Hogan and Fisher (2006) revisited their study to find out and compare how users manage their E-mail in 1996 and in 2006. Initially a little evidence of distinct strategies was seen in handling/organizing their E-mails. They collected data from employees of technology company using SNARF prototype (Social Network and Relationship Finder). The total number of samples contained 600 participants. They created a scale for measuring `E-mail Overload’ to help researchers and they also state that the term ‘E-mail overload’ came from Whittaker and Sidner. The term E-mail refers to different functions: as calendar, to-do-list, data archive and contact list. The initial difference between 1996 and 2006 was the size which was 10 times the average size of the inbox in 1996, they found that some aspects were dramatically changed since 1996 such as size of the archive, average inbox size, number of folders the users used.
The expression "overload" has been comprehensively reinterpreted since as the feeling of being overpowered by E-mail. While a few sources differ, others contend that approaching E-mail conveys such huge number of new tasks that clients cannot stay up with the latest. The notoriety of E-mail controls and systems propose that there is a general worry about overload. Whittaker (1996) utilizes the term `E-mail over load’ to examine three primary E-mail capacities: task management, personal archiving and asynchronous communications.
The research conducted by Grevet et al., (2014) noticed that E-mail inboxes were far more complicated compared to sixteen years before where E-mails contained simple incoming messages. In their research they recruited 19 participants for the study out of which 16 people were interviewed in person and 3 were interviewed remotely through telephone and screen sharing. The age demographics was divided into different categories; i). Three between 18 to 24, ii). Six between 24 to 30, iii). Six between 31 to 40, iv). One between 41 to 50, v). Two between 51 to 60. The research conducted by the same author had a balanced gender representation i.e. 9 females and 10 male participants. The research found that the inboxes were even large now and still contained more incoming unread messages.
Users can be classified based on their E-mail management strategies (whittaker and Sidner 1996, Hogman and Fisher 2006). Whittaker and Sidner (1996) classified users from the perspective of the following; 1. Whether they filed E-mails into folders, 2. How often they filed. Based on these questions users can be categorized as frequent filer’s, spring cleaners who file sometimes, and no filers. Fisher and Hogman (2006) found that users can have multiple strategies to that they combine over time to manage their E-mails, they also added another dimension called number of folders. Some users had many folders with complex nesting structures and some users had many messages per folder. Further Fisher et al. suggests future studies to add another dimension about how users feel in organizing their E-mails and categorize users along these feelings.
2.4 Information Obesity: More individuals can communicate a greater number of things to a bigger number of individuals than has at any point been, perhaps in the past, which prompts information obesity as suggested by Shirky (2007). Whitworth (2009) forms a term called `information obesity’ where large information stacks without the knowledge of the user which leads to information obesity and compares this with physical obesity. According to him physical obesity can be maintained by going to the gym and following a proper healthy diet and in the same way to maintain information obesity, he says that there has to be some educational means to combat information obesity which talks about digital literacy.
2.5 Digital Literacy: According to Eshet (2004) digital literacy involves more than the ability to use or operate a digital device; it includes a large variety of skill set. American library Association defines Digital literacy as “The ability to use information and communication technologies to find, evaluate, create, and communicate information, requiring both cognitive and technical skills" (Heitin, 2016). Buckingham’s (2010) work reveals that all the youngsters' recreation time what they spent before computers/mobile phones and PCs are significantly more than gadgets for information retrieval, they pass on pictures and dreams, open doors for creative self-articulation and play, additionally fill in as medium to trade messages through the web. The web PC diversions, advanced video, cell phones and other contemporary innovations give better approaches for interceding and speaking to the world and of conveying. Outside school, youngsters are connecting with these media, not as innovations but rather as cultural forms. Understanding these forms, said by Buckingham (2010), is Digital literacy.
2.6 Digital Natives and Immigrants: Prensky (2001) came up with the concepts Digital Natives and Digital Immigrants and he explains that these terms as a method for understanding the profound contrasts between youngsters of today and a significant number of their elders. Although these terms were useful, Prensky, suggests that moving into the 21st century in the digital era, these terms become less relevant and there is a need to think about the terms of Digital Wisdom. There are about six terms where Prensky explains to achieve Digital Wisdom in his research work. Digital Wisdom is defined as “Wisdom arising from the use of Digital technology to access cognitive power beyond our innate capacity and to wisdom in the prudent use of technology to enhance our capabilities.”
2.7 Information Retrieval: The technique of obtaining information resources relevant to an information need from a collection of information resources (Giles, nd). With this growth in data of our E-mails every day, there is a need to understand how to search the information which is needed at the right time, which is also called information Retrieval/Seeking/Searching. Information Retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large collections usually stored on computers (Cambridge UP, 2009).
The study concentrates on Gmail services as the University of Sheffield offers Gmail services to students for communication purposes.
Gmail: At the point when Gmail was first introduced, the development was constrained only by allowing users to invite a predetermined number of their companions to open accounts. This let Gmail a chance to maintain the reputation as an elite account and created demand. Gmail was instantly one of the most popular services available at that point, the restricted welcome framework authoritatively finished on February 14th, 2007 (Karch, 2018). Gmail gives four tools for filing E-mails: Labels, which enables clients to label messages (an E-mail can have numerous labels); Archive, which expels messages from the inbox; Move, which appoints a name and chronicles on the double; and Filters which are programmed rules the client needs to indicate. Emails can be filed without names and be found through inquiry. Channels can perform numerous activities, for example, avoiding the inbox, or applying a name yet keeping the message in the inbox, or applying a name yet keeping the message in inbox (Civan et al, 2008). In this research we study participants who are using Gmail services. There are different features in Gmail that can likewise help with overload, for example, split inbox sees where a client can pick what class of messages should appear at the top of the inbox. For instance, with priority inbox clients can see messages that are set apart as critical in the top most box of their inbox, furthermore, clients may add plugins to their inbox through Google labs and third-party apps (Pichai, 2012).
After the review of the existing literature, it is found that E-mail services are very important in one’s life as communication, storage and multiple purpose tool. But the overload issue exists till today from since the E-mail services was established. To explore this issue and to come up with suggestions to avoid overload there were number of studies conducted by different researchers. The initial research was conducted by Whittaker and Sidner in 1996 by examining 20 participants who were employees, they found that overload exists and came up with few suggestions to avoid E-mail overload, later after ten years Hogman and fisher in 2006 replicated Whittaker and Sidner’s research with a sample of 600 participants. They found a huge difference in the inbox sizes which was more compared to 1996. Later on, in 2014 after sixteen years of Whittaker and Sidner’s research Grevet et al. recruited 19 participants for the study based on different age groups found that the inboxes were even larger and complicated with too many unread incoming messages after the advancement of E-mail services compared to 1996.
Almost all the research studies carried out in the area are based on the participants in general or employees working for some organization. But there is a gap in the research as there is not much research carried on whether students face the overload issue or not. This research aims to study the overload issue with students of the University of Sheffield as the research participants. However, there are several methods offered by E-mail services to combat E-mail overload. The present study tried to investigate whether students are successful in combating the overload issue or not.
CHAPTER-3: METHODOLOGY
3.1 Introduction: The overall objective of this research is to find out whether students of the University of Sheffield face E-mail overload or not. In case, if they are facing it, it is an effort to know how they are coping with it. If they are successful in avoiding overload, it is intended to explore what methods they use to manage it. And also explore the ways and means they used to manage and also to understand whether they are efficient or not.
The specific research objectives are stated in the Chapter-I, which are formulated as research questions, the same questions are stated as follows;
RQ-1: Whether E-mail overload exists with the students of the University of Sheffield in the present juncture?
RQ-2: If it exits is there any difference between various categories of students (UG, PG and Ph.D.) in organizing E-mails to avoid overload.
RQ-3: Whether the students of the University of Sheffield University are successful in rationalising their inboxes?
RQ-4: Whether the E-mails from the university are causing information obesity to students?
RQ-5: Are the students facing E-mail stress?
RQ-6: What are the differences between E-mail management in the present and in the past?
To study the objectives or to answer the research questions an effort has been made in this chapter to give the detailed information relating to the research methodology in terms of the research design, data collection, data cleaning, data integration and data analysis procedures. All these exercises are done to present that which is the most suitable method to address the research questions, which are formulated. The practical and theoretical fundamentals are discussed in the following sections.
3.2 Research Design: “Not everything that can be counted counts, and not everything that counts can be counted” (A. Einstein).
Qualitative Research is largely an exploratory research. It is utilized to pick up a comprehension of basic reasons, suppositions, and inspirations. It gives bit of knowledge into the issue or creates thoughts or theories for potential quantitative research, Qualitative Research is additionally used to revel drifts in thought and assessments and jump further into the issue. Qualitative information is to gather the strategies and utilizing unstructured or semi-organized methods. Some regular strategies combine all the gatherings in singular meetings, and by observing interest/perceptions. The example of the measure is normally little, and the respondents are chosen to satisfy a given standard (Susan and DeFranzo, 2011).
Qualitative vs. quantitative research is utilized to measure the issue by method for producing numerical information that can be changed into usable insights. It is utilized to evaluate states of mind, feelings, practices, and other characterized factors and sum up results from a bigger example of population. Quantitative research utilizes quantifiable information to define actualities and reveal designs in research. Quantitative gathering techniques are significantly more organized than qualitative information and accumulation strategies. Quantitative information accumulation techniques incorporate different types of overviews – online studies, paper studies, versatile studies and booth reviews, up close and personal meetings, phone interviews, longitudinal examinations, site interceptors, online surveys and methodical perceptions (Susan and DeFranzo, 2011).
The following characteristics of quantitative research which are stated in the University of Southern California USC Libraries (2011) are as follows;
• The information is typically accumulated utilizing structured interviews, instruments or questionnaires.
• The results depend on bigger sample sizes that are explanatory of the population.
• The examination study can be usually be replicated or repeated given its high consistency.
• All parts of the study are precisely composed before data is been collected.
• Information is numbers and measurements, frequently organised in tables, outlines, figures or other non-literary structures.
• The research data is very helpful in statistics, often arranged in tabular forms, charts, figures, or other non – textual forms.
• Specialist utilizes devices - for example polls or Personal Computer (PC) programming to analyse and visualise numerical information, which can be very helpful in answering the formulated research questions.
The discussion on quantitative and qualitative methods are very vast subjective ideal models have a long convention and therefore they cannot be thoroughly clarified here. Although they can be summarized as the status of quantitative and subjective strategies as similarly scholastic and recognized, under the condition that exploration is directly efficient and takes after rules, which are established.
This research is a combination of quantitative and qualitative research for the better understanding about the research questions and also to gather the opinions, data and suggestions of the people to summarise them with better suggestions to overcome the overload problem.
3.3 Research Model: The methods used for this research is a replication of Whittaker and Sidner’s 1996 study. The method used is a mixed method which includes both qualitative and quantitative. A structured questionnaire was prepared to collect both qualitative and quantitative data. The research participants were approached physically by the researcher outside the university libraries. The research participants were chosen randomly by explaining them about the research briefly for about a minute. The respondents who are ready to contribute to the research were requested to give the answers to the questions by the researcher and filled by the researcher himself. There are twenty questions in the questionnaire out of which two questions were asked to get the qualitative data and the rest were related to quantitative data.
3.4 Data Collection: In this research to collect the data `The Simple Random Sampling (SRS)’ method was chosen, which is also known as `Random Sampling’, it is one of the most upfront probability sampling strategy. It is also one of the most popular methods for choosing a sample among the universe for a varied range of purposes. In SRS each participant of population is equally likely to be selected as a part of the sample. Gravetter and Forzano (2011) stated that “the logic behind simple random sampling is that it removes bias from the selection procedure and should result in representative samples”.
Some of the advantages discussed by Saunders and Thornhill (2012) of SRS method are discussed as follows;
• If the above stated method is applied correctly, SRS can be dealt by having the least biasness compared to any other methods.
• Data, which is collected through SRS can represent a large population with a small data set.
• The research results and findings from the data collected by using SRS can be generalized to the similar population elsewhere.
Sampling Procedure: The data was collected by the researcher himself by standing outside the university libraries. Every 10th person who comes out of the libraries were approached and requested them to participate in the research. Every day five respondents were interviewed through the structured questionnaire/schedule prepared for the study.
There are few variables identified as the most important restrictions in the sampling procedure: (1) Limited time frame, (2) Geographic restrictions, (3) A limited number of interviews, (4) Some confidential information couldn’t be accessed due to ethical issues. The time frame for the entire dissertation is three months, hence the data collection time was allocated just two weeks, which includes data collection as well as entering data to Comma-Separated Value (CSV) format for analysis. The research is basically based on the students of the University of Sheffield; therefore, the location was restricted only to the university libraries as it was easier for the researcher to meet/get the respondents.
3.5 Interview Technique: The interview process can be called as structured communicative process, where the same questions were asked to each and every participant to extract information, the extracted information by the participant is strongly influenced by the participant. Every interview conducted produced both qualitative and quantitative data which are helpful to analyse and conclude the research.
The technique involved in the interview was the standardized open-ended interview method which consist of a semi-structured questionnaire (Jamshed, 2014) where the questions are predetermined and consisted of 20 questions, each respondents had to answer the same questions in the same way and the same order, and in the last overall feeling about the subject that is about the E-mails were asked and the researcher made a quick note of whatever they said to capture the feelings and opinions of the participants.
In total 40 interviews were conducted with the university of Sheffield students, which are classified in to three categories (UG Students, PG Students, and Ph.D. Students). Of the three categories of the students, Post-Graduation (PG) students constitute 28 respondents, 4 participants were from Under Graduation (UG), 6 participants from Ph.D. and 2 participants did not prefer to say their category.
3.6 Data Coding: Data coding is a technique of coding the observed / collected data in both quantitative / qualitative research, the data acquired is either form interviews or from questionnaires. The motivation behind data coding is to draw out the meaning and importance of the data that respondents have given. The data coder extracts preliminary codes from the questionnaire which makes the analysis more precise and concise to make the analysis more accurate (Sahifa, 2014).
In this research few of the questions were coded to numerical values for the quantitative analysis, which is helpful for more accuracy, the coded values are shown below;
For the following questions Likert scale was used, Likert scale is a measuring scale which is usually used for survey purposes, the scale ranges from one extreme to the other to capture respondent ratings by a series of questions which are asked by the researcher, the ratings start from strongly disagree to strongly agree.
Likert Scale:
Source: https://www.google.com/search?q=likert+scale
Questions which were coded in the form of Likert scale are as follows;
1. Whether you agree that E-mail Notification distracts you?
2. Do you agree that you read E-mails immediately after its arrival?
3. Do you agree that while checking E-mail, you will prioritize important people first?
4. Have you woken up to check E-mails?
5. Do you agree that you check E-mails during dinner?
6. Do you have advanced settings by the respondent to organize E-mails?
7. Do you have difficulties in retrieving E-mail information?
8. Do you agree that you receive E-mails more than needed?
9. Do you agree that you are facing E-mail Overload?
The other questions which were coded are as follows;
1. Age of the respondent?
Code Option given to the respondent
1 Less than 25
2 Less than 35
3 More than 35
4 Prefer not to say
2. Approximately number of years of experience you have using E-mails?
Code Option given to the respondent
1 Less than 5 years
2 More than 5 to Less than 10 years
3 More than 10 years
3. Do you receive E-mail notifications on mobile device?
Code Option given to the respondent
0 No
1 Yes
4. How many hours outside university do you spend checking E-mails?
Code Option given to the respondent
1 Less than 1hr
2 More than 1hr to less than 2hrs
3 More than 2hrs to less than 4hrs
4 More than 4hrs
3.7 Data Cleaning: Data cleaning, which is also called as data cleansing or data scrubbing, manages with spotting and removing errors and irregularities from the data in order to enhance the quality of the data, data quality issues are available in single data accumulation for example, due to missing out some questions during data entry may end up having missing values or invalid data in the data base. If multiple data bases are integrated together the inconsistencies may occur more where data cleaning needs to increase significantly (Broeck et.al, 2005).
In this research Extraction, Transformation Loading (ETL) process was followed. The data was extracted in the form of semi-structured questionnaire, the next step was transforming the data into Microsoft Excel and saved it in the form of CSV and the last stage was normalizing the loaded data. There were some missing values, where participants were not sure about the number of Emails in their inboxes, these rows were normalized by calculating the average by relating to the year they started using the E-mail services. As the data was collected by the researcher himself, there was no much inconsistency in the collected data.
3.8 Tools for the Data Analysis: In this project report the tools used for the analysis are;
• Microsoft Excel
• SPSS
• Tableau
Microsoft Excel: Excel consists of spread sheets or also called as worksheets, each cell can contain any text or number, it also allows users to click any cell and add the data based on the requirement. Excel allows a wide range of formulas which can be applied on the spread sheets for calculation purpose. Microsoft Excel is one of the powerful tools for data analysis, one of the special features provided by excel is the pivot tables. Pivot tables can be used to visualize large sets of data, in addition to this the excel formulas can be used to aggregate data and create meaningful reports (Parson, 2015).
SPSS: SPSS was launched in the year 1968 and then acquired by IBM in 2009, it is a statistical package for Social Sciences and it can be used for various researches and complicated statistical data analysis. SPSS is used by data miners, survey researchers, marketing researchers and so on (Foley, 2018). Some of the statistical methods which are mentioned by Foley (2018) are as follows;
• Descriptive statistics: This method involves in finding out the frequencies, descriptive ratio statistics and cross tabulation.
• Bivariate statistics: This method helps in analysis of variance (ANOVA), which means Correlation of the dataset and nonparametric tests.
• Linear regression is one of the numerical prediction outcomes.
• Other predictions for identifying groups which includes cluster analysis and factor analysis.
Tableau: Tableau is one of the powerful data visualization and business intelligence tool which has a very spontaneous user interface; there is no need for coding knowledge to work in tableau. Tableau plays a very important role in rationalizing the data, producing insightful reports (Tableau, 2018).
CHAPTER-4: RESULTS and DISCUSSION
The forty participants who responded in the survey to gather preliminary data were from the University of Sheffield, the respondents age was categorised where 31 subjects constituting about 77.50 per cent were less than twenty-five years of age, 8 subjects, about 20 per cent, were less than 35 years of age and 1 participant more than 35 years of age (Table- 1). Therefore, it can be concluded that most of the respondents belong to below 35 years of age.
The participants of the study were based on different categories based on the degree what they are pursuing i.e., Undergraduate Students (UG), Post Graduate Students (PG) and the Ph.D. Scholars. By following the simple random sampling method we have got twenty-eight participants from PG category (70 per cent), six from Ph.D category (15 per cent), four respondents from UG (10 per cent) and other two participants who did not disclosed their status in terms of education preferred not to say anything (Figure-1). Therefore, PG students constitute the highest number of students who have come under the sample of this research work.
Nineteen participants (47.50 per cent) had more than ten years of experience in using Emails, seventeen participants (42.50 per cent) had more than five years and less than ten years of experience and four participants had less than five years of experience in using E-mails (Figure- 2). This clearly reveals that most of the respondents have better experience in using E-mails as about 90 per cent have to experience of five to more than ten years.
RQ1: Whether E-mail overload exists with the students of the University of Sheffield in the present juncture?
The first research question pursued to determine if students experiencing E-mail overload or not in the present after the updates and facilities provided by E-mail services to avoid overload. In order to answer this question various answers were analysed provided by the participants to answer the above question.
The participants were given a small introduction about what E-mail overload is, about 80 per cent of the subjects knew about overload and were asked whether they are facing E-mail overload or not.
Nine participants strongly agreed, seven participants agreed, and ten participants slightly agreed that they are facing E-mail overload (Figure- 3). In total 26 participants, whatever the degree of acceptance have opined that there is email overload, which constitutes about 65 per cent of the total sample. Hence, it can be concluded that the problem of email overload persisted in the student of the University of Sheffield.
The same figure-3 reveals that there was one participant who Strongly disagreed, six participants who disagreed, and 7 participants who slightly disagreed to E-mail overload. Fourteen respondents constituting 35 per cent of the sample students, with whatever the degree, they have disagreed that there is email overload.
Further to have a clear picture of how many participants agrees to overload the Likert scale was grouped as follows;
• 1-3 as Disagreed and coded as 1 • 4-6 as Agreed and coded as 2
About 65 per cent of the participants felt that their E-mails are overloaded where they either slightly agreed, agreed or strongly agreed to overload. Whereas 35 per cent of the participants disagreed to overload (Chart- 1). Therefore, it can be inferred that overload still exists in a larger population, but we also infer that 35 per cent of the participants are able to avoid E-mail overload with various strategies which will be discussed further in the report.
A correlation matrix was drawn between to understand, whether the respondents agreed
that they received E-mails more than needed and in turn facing E-mail overload.
A significant positive correlation was seen between the two variables (Table-2.), with a
Pearson Correlation value which is 0.565, where the p value is 0.000 which is < 0.5 indicating a
moderate relationship between feeling more E-mails received and facing E-mail overload.
Pearson’s r value (degrees of freedom) is N-2 (40 -2) which is r (38) = 0.565, p=0.000.
Out of the total 40 respondents there were only eight participants who didn’t feel that they had E-mail overload due to some precautionary measures what they have taken to avoid, the details, which are discussed in the later part of the report, but the maximum respondents i.e., thirty two participants felt that they experience E-mail overload at least once a week (Chart- 2).
RQ2: If it exits is there any difference between various categories of students (UG, PG and Ph.D.) in organizing E-mails to avoid overload.
The Table-3 clearly reveals that of the 28 PG respondents 15 students constituting 53.57 per cent have been using advanced settings to organize their E-mails. Thirteen respondents constituting about 46 per cent are not using the advanced techniques to organize their E-mails. Interestingly of the six Ph.D. students, four respondents have been using advanced techniques in organizing their E-mails. Only two students had disagreed that they do notuse any advanced settings to organize their E-mails. Majoring of the UG students constituting about 75 per cent (three respondents) are not using any advanced technology. This clearly indicates that as the education level increases the students will be using advanced technology in managing their Emails.
This question primarily expected to know how the students organize their E-mails. The qualitative answers reveal that there are few differences between the techniques used by different categories of students to manage/organize E-mail overload.
Undergraduate (UG) students are not comfortable with the current settings and they are not using the settings available in the E-mail services (see Table-3), they feel that they need more advanced settings to avoid overload, whereas there are Post Graduation (PG) and Ph.D. students mentioned various techniques to avoid overload as shown in Table-4.
RQ3: Whether the Sheffield University students are successful in rationalising their inboxes?
The total number of E-mails in the respondent’s inboxes ranged from less than 100 to more than 5000 as can be seen in the Table-5. The PG students manage to maintain their inboxes with less than 600 E-mails in their inboxes whereas UG and Ph.D. students had more than 1000 E-mails which looked like overloaded in the span of maximum four years. This has led to the question on how students are managing their inboxes with only the E-mails they needed.
Qualitative analysis was helpful in finding answers to the above question. Out of forty sample students about eighteen students answered that they either unsubscribe, delete unwanted, once marking the important E-mails. The answers given by various categories of students are different and therefore, they are categorized and presented in the Table-6. The table clearly reveals that the PG students put lot of effort to reduce the email burden through various measures.
The above information has led to one more question, i.e., whether the sample students are able to retrieve data they want without difficulties. Towards these about 62 per cent of the respondents disagreed to difficulties faced to retrieve the data. The use of the Search made very helpful in retrieving the data. About 32 per cent of the respondents have faced the difficulties in retrieving data due to overload. All these can be seen clearly in the Chart-3. Though majority of the sample students are not facing the difficulties in retrieving the emails but still considerable percentage of sample students have been facing the difficulties in retrieving the emails. With this one can say that `emails retrieving’ is a challenge for the students.
RQ4: Whether the E-mails from the university are causing information obesity to students?
The number of emails received by the respondents ranged from two to twenty emails in a day - where the respondents did not feel that university emails are causing information overload because the university emails are important and less emails received, Mean, Median Std. Deviation of emails received for a day are shown in the Table-6 below.
The qualitative analysis was very helpful in digging deep into why the E-mails are getting overloaded for the university students, UG participant No. 20 (in the list of the sample) said that “Unwanted E-mails and Adds makes overloaded due to online shopping”, PG students No. 9, 10, 19, 21, 22, & 23 all came up with the same answers that Adds and unwanted E-mails are making them overloaded, and one Ph.D. student felt that unwanted E-mails are the E-mails received from other departments and adds makes overloaded (see Table-7).
RQ5: Are the students facing E-mail stress?
To find answers for this question various research variables were studied and analysed, which are discussed as follows;
Initial analysis found out that 32 participants constituting about 80 per cent of the student participants spend less than one hour after hours to check their emails (see Table-8). Seven respondents have mentioned that they spend one to two hrs. after hours to check the emails. The table clearly reveals that whatever the intensity the students are working after hours to check their emails, which come from the university.
When the participants were asked about why they check E-mail after hours, 25 per cent of the
respondents have said that they check because they felt that it is productive and only seven per cent of
the sample students felt that they are frustrated but even then they still check their E-mails as they do
not want to lose important E-mails or they want to stay connected to the university or they feel that it
helps them to organize and plan (Chart - 3). However, the maximum sample students i.e. 68 per cent of
the sample expressed neutrality about checking their E-mails after hours (see Chart-3).
No matter what category of the students are studying, they check their E-mail outside hours and
know that E-mails are very important in one or the other way, which directly or indirectly helps them
(Figure-4). The figure given below clearly indicates that about 17 participants (42.50 per cent) have said
that they do not want to lose important E-mails, fourteen of them (35 per cent) feel that it is helpful for
them as they are being connected to the university and nine of them feel that it helps them to organize
and plan their schedule. Hence it can be concluded that the students of the university keep checking
their E-mails even after hours as they find advantages in it.
Figure-5 clearly includes the effects of using emails. The effect is basically influence on close
relationship; impact on ability to learn, remember, and absorb; affects the ability to relax, causes stress
and anxiety, close relationship and causes stress anxiety, remembrance, absorb and ability to learn. All
these together constitute about 57.50 per cent. This means that about 23 respondents have one or the
other effect for having used the E-mails after hours in the university. Of these 23 respondents, nine
respondents have stress related issues due to E-mails after hours. However, about 42.50 per cent i.e.
seventeen subjects of the sample weren’t affected by the overload issue.
RQ6: what are the differences between E-mail management in the present and in the past?
Based on the qualitative analysis few participants said on how they felt about the E-mails in the past. A student belonged to Ph.D.: student participant No.25, has said that in the past he felt that, without the search bar it was hard to retrieve data if overloaded. Student No.29 felt that the replies to E-mails were slow compared to the present situation as there was room for mobile notifications.
PG student participant No.4 felt that using folders and creating threads made managing Emails easier, and the student No.9 felt that the updates now are making much easier to use compared to the past (Table-9). The same Table-9 reveals that the 15th Respondent Number, had views of not having E-mail overload in the past as E-mails were used only to get official E-mails which made easy to retrieve the data. He/She has said in his/her own words as “Limited E-mail in your inbox made easy to retrieve”.
Thirty-two Respondents agreed that they prioritize important people/E-mail which is one of the reasons they are able to manage overload, the numbers and their choice of prioritization is shown below (see Table-10).
Figure-6 gives us a clear picture of the number of people agreed to prioritize and the number of people disagreed to prioritization on E-mails.
CHAPTER-5: RECOMMENDATIONS
E-mail:
In most professional situations, E-mail has taken over as postal mail and phone calls. The considerable volume and differed nature of E-mail messages make challenges past a basic hierarchical documenting structure. The data conveyed through E-mail has numerous reasons, media, composing styles, lengths, connections, senders/recipients, and other novel characteristics. The accompanying suggestions depend on the data administration writing and practices recognized by the researcher based on reviewing respondents.
To overcome E-mail overload and manage the inboxes few effective practices can be followed, a number of suggestions can be formed for students as well as every individual to maintain their personal information regarding E-mails.
There were few of the students using advanced settings and techniques to overcome E-mail overload however, they were not fully successful in overcoming E-mail overload. To tackle Email-overload with the use of advanced settings there are few more techniques to be followed in order to overcome this issue, based on the study, the strategies are discussed as follows;
Based on the research carried out, there were very few students who could easily manage and avoid E-mail overload by following few techniques, some of them are as follows;
• Spending about 2-4 hours of time every day in reviewing their E-mails and organizing them, the time spent should be divided in specific intervals: Example: 30 min. when you wake up, and 45 min. over the day and 45 min. after dinner sorting the E-mails and deleting unwanted E-mails can help the issue.
• Having few Advanced settings provided by the E-mail services like spam filters, auto deleting unwanted E-mails, use of labels, tagging techniques, use of pre-configured batch filtering deletion can be used to detect unwanted E-mails and filters them right away is a good habit to follow, along with these marking important E-mails and creating folders could help tackle overload problem.
• Spending a good amount of time in the weekends to organize the E-mail inbox and checking out all the E-mails once again, which were received in the following week makes an individual not lose any important E-mail.
• Checking the E-mails as soon as its arrival, through mobile having their mobile notifications turned on, and categorise according to the choice, if it is an unwanted E-mail deleting it right away is the best choice according to few respondents who managed to overcome overload.
• Ignorantly/innocently writing your E-mail address everywhere is the major cause of having unwanted E-mails in the inboxes, every individual must be very careful about the personal information before they share with anybody, there was one respondent who said “due to online shopping and not concern about their E-mail ids and writing them everywhere” are the causes for unwanted E-mails sometimes. Therefore, avoid writing your email Ids, in an unwanted places and circumstances. The Ids have to be given only on demand from the customer/client.
• It is recommended that having different E-mail Ids for different purposes, can be helpful in having a smaller number of E-mails in the inboxes. For Example: having a different account for work and different for family/ friends makes your official E-mails filter right away into a different account. In this method, the respondent has the less chances of losing important E-mails.
• Creating threads for the people with whom you have very frequently converse will help and makes you to have every conversation dated and this makes you to sort your inbox in a clean and efficient way.
Few more recommendations are discussed below for the sender and the receiver of the E-mails to have and better manage E-mails. These recommendations are made based on the discussions with the sample respondents only. Since these opinions could not be tabulated the same are given in a write as recommendations.
To the Sender:
• The subject line is very important in an E-mail, as the reader sees the subject line when notified, if the receiver doesn’t feel it important the E-mail may be ignored.
• When replying to a chain of messages, sender must consider changing the subject to reflect the new E-mail, changing the subject may be helpful in organizing the inboxes.
• When writing an important E-mail make your important line first, so that the reader considers its importance and you may get a quick response.
To The Receiver:
• E-mails must be dealt in a strategic way, use of delete, act, flag, mark important and star have to be used carefully. Most importantly the E-mail inbox has to contain only the messages, which require action.
• All the E-mails which are important have be added to folders, which makes retrieval of the E-mails easy and quick.
• All the unwanted and advertisement E-mails have to be considered and deleted taking time and unsubscribing them would help to have clean inboxes.
CHAPTER-6: CONCLUSIONS
It is advised that the information overload is one of the important challenges of the present day in the internet, where internet and smart phones are available for almost every individual, according to Milpitas (2017) the number of implementations have jumped to 72 per cent since June 2016. Information is as old as the internet, but information overload can be dealt very effectively by using number of filter mechanisms in a professional way, whereas when it comes to PIM every individual deal with his information in a different way, sometimes the information gets overloaded due to the inefficient way they deal with their data. One of the problems for individuals is managing their E-mail inboxes when there are too many incoming messages overloading their inboxes. In the entire world in general and the University of Sheffield in particular every individual/student deal with their E-mails in a different way. This research was proposed to check the students of the University of Sheffield how they manage their E-mail inboxes and also try to find out the efficient way to deal with them to avoid E-mail overload. The literature review revealed that there is gap in the study as there is no much research conducted to find out the user behaviour of the individuals. It was clearly evident that individuals who felt that they are receiving E-mails more than needed had E-mail overload issues, out of which 32 per cent of the sample had no issues of E-mail overload problems as they use professional techniques to manage their E-mails. The rest 68 per cent were facing E-mail overload and facing difficulties in retrieving the data they needed and sometimes even the important E-mails are lost in the large inboxes. Though they use few techniques to manage overload issue, but they are not able to cope up with it due to the flaws in managing or the advanced settings they are using.
Finally, it was clearly evident that every individual knows the importance of E-mails and E-mail services. The individual/individuals feel that it is very useful and important to service and to communicate to the world and save their work in the drive which can be accessed anywhere from the world. Some-times individual feels the E-mail stress due to the inability to manage their E-mails and spending a lot of time searching the information they need.
The present study based on the sample of 40 respondents clearly proved that there exists E-mail overload still and few advanced techniques are explained and given as recommendations in the Recommendation chapter the advanced settings and techniques followed by the individuals who use it to overcome overload and were successful in avoiding overload are also explained in the same chapter.
Finally, to conclude, E-mail service is one of the powerful and sophisticated way to communicate in the professional world. Therefore, every individual has to spend some quality time to refine their inboxes with the techniques explained above or else they may fail to have a grip over it and tend to lose important E-mails in the large inboxes. This, in turn, may lead to a chance of feelings of stress when individual face difficulties in retrieving the information when needed. Therefore, the individuals who are depending on the emails in their studies, business and such other areas they need to be careful.
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Appendix: Ethical Approval letter:
